Solutions Manual For Data Visualization Exploring and Explaining with Data 2nd Edition By Jeffrey Ca

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 1: INTRODUCTION

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1

END OF SECTION PROBLEM SOLUTIONS 1.

Types of Analytics. Indicate which type of analytics (descriptive, predictive, or prescriptive analytics) each of the following represents. LO 1 a. a data dashboard b. a model that finds the production schedule that minimizes overtime c. a model that forecasts sales for the next quarter d. a bar chart e. a model that allocates your financial investments to achieve your financial goal Solution: a. descriptive b. prescriptive c. predictive d. descriptive e. prescriptive

2. Transportation Planning. An analytics professional is asked to plan the shipment of a product for the next quarter. She employs the following process: Step 1. For each of the 12 distribution centers, she plots the quarterly demand for the product over the last three years.

Step 2. Based on the plot for each distribution center, she develops a forecasting model to forecast demand for next quarter for each distribution center.

Step 3. She takes the forecast for next quarter for each distribution center and inputs those forecasts, along with the capacities of the company’s four factories and transportation rates from each factory to each distribution center, into an optimization model. The optimization model suggests a shipping plan that minimizes the cost of how to satisfy the forecasted demand from the company’s four different factories to the distribution centers.

Describe the type of analytics being utilized in each of the three steps outlined above. LO 1

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

Solution: Step 1. Data visualization is descriptive analytics.

Step 2. A forecasting model is predictive analytics.

Step 3. An optimization mode is prescriptive analytics.

3. Wall Street Journal Subscriber Characteristics. A Wall Street Journal subscriber survey asked a series of questions about subscriber characteristics and interests. State whether each of the following questions provides categorical or quantitative data. LO 2 a. What is your age? b. Are you male or female? c. When did you first start reading the WSJ? High school, college, early career, midcareer, late career, or retirement? d. How long have you been in your present job or position? e. What type of vehicle are you considering for your next purchase? Nine response categories for this question include sedan, sports car, SUV, minivan, and so on.

Solution: a. quantitative b. categorical c. categorical d. quantitative e. categorial 4. Comparing Smartwatches. Consumer Reports provides product evaluations for its subscribers. The following table shows data from Consumer Reports for five smartwatches on the following characteristics: Overall Score—a score awarded for a variety of performance factors Price—the retail price Recommended—does Consumer Reports recommend purchasing the smartwatch based on performance and strengths?

Best Buy—if Consumer Reports recommends purchasing the smartwatch, does it also consider it a “best buy” based on a blend of performance and value?

For each of the four pieces of data, indicate whether the data are quantitative or categorical and whether the data are cross-sectional or time series. LO 2 Make

Overall Score

Recommended

Best Buy

Price

Apple Watch Series 5

84

Yes

No

$395

Fitbit Versa 2

78

Yes

Yes

$200

Garmin Venu

77

Yes

No

$350

Fitbit Versa Lite

65

No

No

$100

Solution: Overall Score and Price are quantitative. Recommended and Best Buy are categorical (both are yes or no). All of these data are cross-sectional.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

5. House Price and Square Footage. Suppose we want to better understand the relationship between house price and square footage of the house, and we have collected house price and square footage for 75 houses in a particular neighborhood of Cincinnati, Ohio, from the Zillow website on January 3, 2021. LO 2, 3 a. Are these data quantitative or categorical? b. Are these data cross-sectional or times series? c. Which of the following type of chart would provide the best display of these data?

Explain your answer. i. Bar chart ii. Column chart iii. Scatter chart Solution: a. House price and square footage are quantitative. b. The data were collected at a single point in time, so these data are cross-sectional. c. iii Bar charts and column charts are better for categories. Here we do not have categories, we have pairs of numerical data for each of 75 houses (price, square footage). Therefore, a scatter chart with square footage as the horizontal axis and price as the vertical axis would be appropriate.

6. Netflix Subscribers. The following chart displays the total number of Netflix subscribers from 2010 to 2019. LO 1, 2, 3

a. Are these data quantitative or categorical? b. Are these data cross-sectional or time series? c. What type of chart is this?

Solution: a. Number of Netflix subscribers is quantitative. b. Since these data are collected at several points in time, they are time series data. c. This is a column chart.

7. U.S. Netflix Subscribers. Refer to the previous problem. Suppose that in addition to the total number of Netflix subscribers, we have the number of those subscribers by year for the years 2010–2019 who live in the United States. Our message is to emphasize how

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

much of the growth is coming from the United States. Which of the following types of charts would best display the data? Explain your answer. LO 2, 3 i. Bar chart ii. Clustered column chart iii. Stacked column chart iv. Stock chart Solution: A stacked column chart is most appropriate here as it will show the total number of subscribers (height of the column) but also the same for U.S. subscribers (denoted by color within a column).

8. How Data Scientists Spend Their Day. The Wall Street Journal reported the results of a survey of data scientists. The survey asked the data scientists how they spend their time.

The following chart shows the percentage of respondents who answered less than five hours per week or at least five hours per week for the amount of time they spend on exploring data and on presenting analyses. LO 2, 3, 4

a. b. c. d.

Are these data quantitative or categorical?

Are these data cross-sectional or time series?

What type of chart is this?

What conclusions can you make based on this chart?

Solution: a. These data are categorical: exploring data and presenting analysis; less than or equal to four hours per week or at least five hours per week. b. These data are cross sectional since the survey was administered to a person at one point in time. c. The chart is a clustered bar chart (also known as a side-by-side bar chart). d. Data scientists spend more time exploring data than presenting results.

9. Industries in the Dow Jones Industrial Index. Refer to the data on the Dow Jones Industrial Index given in Table 1.3. The following chart displays the number of companies in each industry that make up this index. LO 3

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

a. What type of chart is this? b. Which industry has the highest number of companies in the Dow Jones Industrial Index?

Solution: a. This is a bar chart. b. Financial Services and Technology each have five companies in the Dow Jones Industrial Index.

10. Job Factors. The following chart is based on the same data used to construct Figure 1.3.

The data are percentages of respondents to a survey who listed various factors as most important when making a job decision. LO 3, 4

a. What type of chart is this? b. What is the fifth most-cited factor?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

Solution: a. This is a column chart. b. The fifth most-cited factor is Industry (Day-to-day Work and Flexible Schedule tie for fourth).

11. Retirement Financial Concerns. The results of the American Institute of Certified Public Accountants’ Personal Financial Planning Trends Survey indicated 48% of the clients had concerns about outliving their money. The top reasons for these concerns and the percentage of respondents who cited the reason were as follows. LO 3, 4

a. What type of chart is this? b. Only 48% of the survey respondents had financial concerns about retirement (outliving their money). What percentage of the total people surveyed had retirement healthcare cost concerns?

Solution: a. This is a bar chart. b. 77% of 48% is 0.77x0.48 = 0.3696 or 36.96%.

12. Master’s Degree Program Recruiting. The recruiting process for a full-time master’s program in data science consists of the following steps. The program director obtains email addresses of undergraduate seniors who have taken the Graduate Record Exam (GRE) and expressed an interest in data science. An email inviting the students to an online information session is sent. At the information session, faculty discuss the program and answer questions. Students apply through a web portal. An admissions committee makes an offer of admission (or not) along with any financial aid. If the person is admitted, the person either accepts or rejects the offer. Consider the following chart. LO 3, 4

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

a. What type of chart is this? b. Which of the following is the correct interpretation of the 21% for Enrolled? i. Of those who were sent an email, 21% enrolled. ii. Of those who were admitted, 21% enrolled. iii. Of those who applied for admission, 21% enrolled. iv. None of the above Solution: a. This is a funnel chart. b. i.

13. Chemical Process Control. The following chart is a quality control chart of the temperature of a chemical manufacturing process. What observations can you make about the process? LO 3

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

Solution: The process appears to be in control. Only one point is outside the control limits (hour 11), and it barely exceeds the upper limit. However, the last five data points exhibit an upward trend and might be cause for concern. The temperature should be monitored closely moving forward.

14. Buying a Used Car. The following chart shows data for a sample of 18 used cars of the same brand, model, and year. LO 2, 3, 4

a. Are these data quantitative or categorical? b. What type of chart is this? c. How might you use this chart to find a used car to purchase?

Solution: a. Price and mileage are both quantitative. b. This is a scatter chart. c. You could identify a potentially good deal by looking for low mileage (to the left on the horizontal axis) and low price (lower on the vertical axis). Two potential good deals are shown in the following chart (circled and in red).

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 1: Introduction

15. Tracking Stock Prices. The following high-low-close stock chart gives the stock price for Exxon Mobile Corporation over a 12-month period. The data are the low, high, and closing price per share on the first trading day of the month. What can you say about the stock price and volatility of the stock price over this 12-month period? LO 3

Solution: As the closing stock price dropped in months 8–10, the price became more volatile as evidenced by the longer bars (the range from low price to high price). The volatility of the price appears to be decreasing in months 11and 12.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 2: SELECTING A CHART TYPE

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1 CONCEPTUAL ............................................................................................................................. 1 APPLICATIONS.......................................................................................................................... 15

END OF SECTION PROBLEM SOLUTIONS CONCEPTUAL 1.

Sales by Region. Consider the following data for percentage of sales by region.

LO 3 Percentage of Sales Region Total Sales East 28% North 14% South 36% West 22% a. Should a bar chart or a pie chart be used to display these data? Explain. b. List two ways to enhance the formatting of the chart to improve interpretability.

Solution: a. These data would be best displayed as a bar chart. Bar charts are preferred over pie charts because we can more easily distinguish differences in length than area or angle. b. The chart should be sorted from high to low based on the percentage of sales. Labels at the end of the bars indicate the exact percentage. Sorting allows the audience to quickly ascertain the rank order of the regions’ contribution to total sales. This is better than a pie chart because it is easier to determine differences in length rather than differences in angle and area.

2. Academic Makeup of Departments. You are conducting an analysis of the makeup of the departments in your firm. Your goal is to compare the departments’ mixes of academic backgrounds. You have defined the following categories for academic background: Business, Engineering, and Other. You have the percentage of employees in each category for each of the four departments as shown in the table below. LO 3

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Department

Business

Engineering

Other

84%

0%

16%

B

45%

43%

12%

C

48%

20%

32%

D

17%

68%

15%

A

What type of chart is best suited to display these data?

Solution: A stacked column chart with the horizontal axis representing the departments and the bars giving the composition of each department of the three categories is the best choice.

Another possibility is a clustered column chart with separate columns for each department-category combination, but that would be more cluttered.

3. Charts of Gasoline Prices. The following charts both show the average price (in dollars) per gallon of gasoline in the United States for 36 consecutive months. Consider the following charts. The first is a line chart and the second is a column chart. LO 3

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Which better displays the data? Why? i. Line chart ii. Column chart Solution: i. Both charts accurately display the data, but the line chart is preferred because it is much less cluttered and allows the audience to easily see the increases and decreases in prices.

4. Pickup Truck Sales. The following charts display the sales of pickup trucks in the United States by manufacturer for one year (source: The Wall Street Journal). You must choose one of these charts to edit to produce the final chart for your presentation to management. LO 3, 5

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Which chart is best for displaying these data? Explain your answer. i. Column chart ii. Pie chart iii. Bar chart vi. Funnel chart Solution: iii. For reasons discussed in the chapter, the pie chart is not a good choice. The funnel chart is inappropriate because there is no natural decrease in a process as is intended for that chart type. The bar chart or the column chart are viable options. The bar chart is the best choice as the labels are not split across lines as they are in the column chart.

5. NCAA Women’s Basketball. Since 1994, the NCAA Division I women’s basketball tournament has had a starting field of 64 teams and, over the course of 63 singleelimination games, a champion is determined. The following two charts (a funnel chart and a bar chart) show how the tournament progresses from the starting field of 64 teams.

LO 3

Which chart best conveys these data? Why? i. Funnel chart ii. Bar chart

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: i. The funnel chart. It is a better choice here as it conveys the natural narrowing of the field as the tournament progresses.

6. Worldwide Robot Supply. The International Federation of Robotics estimates the worldwide supply of industrial robots each year (ifr.org). The charts below show estimates of the worldwide supply of industrial robots for the years 2009 to 2021. The data are shown in two different charts below, first is a line chart and the second a column chart.

LO 3

Which chart best displays these data? Why? i. Line chart ii. Column chart

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: ii. The column chart is preferred as there is a relatively small number of columns, so it is not too cluttered, and this chart also includes labels of specific values.

7. R&D Project Portfolio. The Ajax Company uses a portfolio approach to manage their research and development (R&D) projects. Ajax wants to keep a mix of projects to balance the expected return and risk profiles of their R&D activities. Consider a situation in which Ajax has six R&D projects as characterized in the following table.

Each project is given an expected rate of return and a risk assessment, which is a value between 1 and 10, where 1 is the least risky and 10 is the riskiest. Ajax would like to visualize their current R&D projects to keep track of the overall risk and return of their R&D portfolio. LO 3 Project 1 2 3 4 5 6

Expected Rate of Return (%) 12.6 14.8 9.2 6.1 21.4 7.5

Risk Estimate 6.8 6.2 4.2 6.2 8.2 3.2

Capital Invested ($ Millions) 6.4 45.8 9.2 17.2 34.2 14.8

Which of the following chart types would be the most appropriate for these data? Explain your answer. i. Stacked bar chart ii. Line chart iii. Bubble chart iv. Funnel chart Solution: iii. A bubble chart is most appropriate, as the data are three quantitative variables.

8. E-Marketing Campaign. Gilbert Furniture has initiated a new marketing campaign for its high-end desk lamp. The analyst for e-commerce, Lauren Stevens, has been tracking the progress of the campaign and has collected the following data based on an email sent to the customer list: 68% opened the email, 29% clicked on the web link in the email, 11% added the desk lamp to their cart, and 9% purchased the lamp. LO 3 Which of the following is the most appropriate chart for these data? i. Funnel chart ii. Stacked bar chart iii. Line chart iv. Bubble chart Solution: i. A funnel chart is most appropriate as it conveys the natural progression of the customer reactions from an email advertisement.

9. Choosing the Best Chart Type. Choose the most appropriate chart type (bar chart, bubble chart, choropleth map, line chart) for each data set described below. Use each chart type exactly once. LO 3

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

a. b. c. d.

Advertising budget, number of salespeople, percent of market share for 10 products Annual demand for potato chips (in tons) in the United States by state Annual sales in millions of dollars for seven regional salespeople Population of the United States for each year 1900–2020

Solution: a. Bubble chart, b. Choropleth map, c. Bar chart, d. Line chart 10. Disney Ticket Prices. The three charts below show the price of a general admission ticket to Walt Disney World for the years 2000 to 2020. The first is a bar chart, the second is an area chart, and the third is a scatter chart. LO 3

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Which type of chart best displays these data? Why? i. Bar chart ii. Area chart iii. Scatter chart Solution: iii. Scatter Chart. The bar chart is not natural in that the vertical axis is time when generally we make the horizontal axis time. It is also very cluttered. The area chart is also very cluttered. The scatter chart is simple to read and less cluttered.

11. Exploring Private Colleges. For a sample of 103 private colleges, data have been collected on year founded, tuition and fees (not including room and board), and the percentage of undergraduates who obtained their degree within six years (source: The World Almanac).

The following two charts plot tuition versus year founded, and graduation rate versus year founded, respectively. LO 4

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

a. The two charts are the same type of chart. What type of chart are these? i. Line chart ii. Scatter chart iii. Stock chart iv. Waterfall chart b. Which of the following statements best describes the relationship between tuition and year founded? i. Private colleges founded before 1800 are expensive, but there are greater differences in tuition for private colleges founded after 1800. ii. There is no apparent relationship between year founded and tuition for private colleges. iii. The newer the private college, the higher the tuition. c. Which of the following best describes the relationship between graduation rate and year founded? i. There is no apparent relationship between year founded and graduation for private colleges. ii. The newer the private college, the higher the graduation rate. iii. Private colleges founded before 1800 have high graduation rates, but there are greater differences in graduation rate for private colleges founded after 1800.

Solution: a. ii. b. i. c. iii.

12. Vehicle Production Data. The International Organization of Motor Vehicle Manufacturers (officially known as the Organisation Internationale des Constructeurs d’Automobiles, OICA) provides data on worldwide vehicle production by manufacturer. The following three charts, a line chart, a line chart with a table, and a clustered column chart, show vehicle production numbers for four different manufacturers for five recent years. LO 3

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Which type of chart best displays these data? Why? i. Line chart ii. Line chart with table iii. Clustered column chart with table Solution: ii. The line chart with table is preferred as it clearly depicts trends over time and provides specific values for comparison.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

13. Smartphone Ownership in Emerging Countries. Suppose we have the following survey results regarding smartphone ownership by age in emerging countries. LO 3, 4 Age Category 18-24 25-34 35-44 45-54 55-64 65+

Smartphone (%) 49 58 44 28 22 11

Other Cell Phone (%) 46 35 45 58 59 45

No Cell Phone (%) 5 7 11 14 19 44

a. Which of the following charts best displays these data? i. Stacked column ii. Clustered column b. Is the following statement true or false? Older people are less likely to own a smartphone than a different type of cell phone than younger people.

Solution: a. i. The stacked column chart better illustrates the relative percentages as part of the whole. b. True

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

14. Home Goods Demand. In supply chain planning, demand is often measured in pounds shipped. The following choropleth map shows the demand for home goods, measured in millions of pounds shipped for each state in the United States. LO 4 a. Which five states have the highest demand? b. Compare this map with Figure 2.19, which shows estimates of state population. Does the demand for home goods appear to be related to population? Explain.

Solution: a. California, Illinois, Florida, New York, and Texas have the most demand. b. Demand seems to be correlated with population. The states listed above are also heavily populated as illustrated by the darker shading on both maps in these areas.

15. Coca-Cola Stock Prices. The following stock chart shows stock price performance for Coca-Cola over a two-week period. Note that May 16 and May 17 are a Saturday and a Sunday and are non-trading days. LO 4

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

a. b. c. d.

What type of chart is this?

Which day seems to have the most intra-day price variability?

What is the closing price on May 22?

If you bought 100 shares at the closing price on May 19 and sold all of those shares at the closing price on May 22, how much did you gain or lose (ignoring any transaction fees)?

Solution: a. High-Low-Close Stock Chart b. May 15 appears to have the longest bar and hence the most intra-day variance. c. $45.03 d. 100(45.03-44.54) = -$49 This is a gain of $49.

16. Day Trading. In addition to the high, low, and closing price, an open-high-low-close stock chart uses the opening price per share to give an indication of the net change in the stock price from open to close on a given day. This is designated by a box inside the high-low range. The range of the box is determined by the opening and closing price per share. A black box indicates a loss and a white box indicates a gain for that day. The length of the box indicates the magnitude of the loss or gain in share price. The following chart is an open-high-low-close chart for a two-week period for Coca-Cola. Note that May 16 and May 17 are a Saturday and a Sunday and are non-trading days.

Day trading is the practice of purchasing and then selling stock within the same day. As a novice day trader, your strategy is to buy at the start of the day and sell at the end of the day. LO 4

For which days would you have a gain, and which would you have taken a loss (ignoring transaction costs) for the Coca-Cola data shown in the chart?

Solution: Loss on May 11, 12, 13, 15, 19, 21 and 22. Gain on May 14, 18, and 20.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

APPLICATIONS 17. Smart Speaker Usage. Futuresource Consulting conducted a survey of owners of smart speakers to better understand how they use these devices (source: The Wall Street Journal). The file smartspeaker contains the percentage of the respondents who use their smart speaker for each of 11 activities. LO 1, 2, 4 Use Category

Percentage of Respondents

Checking sports

27%

Checking the news

40%

Checking weather/traffic

49%

Controlling lighting

26%

Finding local information

30%

Fun stuff (jokes, etc.)

36%

Listening to music

74%

Looking up facts

39%

Making phone calls

24%

Setting reminders/alarms

35%

Using a kitchen assistant

24%

a. Construct a bar chart that shows the percentage of respondents by category. Use “How People Use Their Smart Speakers” for the chart title. Edit the chart to make it easier to interpret. Add data labels. b. Sort the data so percentages are ordered from smallest to largest, and note the differences in the corresponding chart. c. Of the categories in the survey, which is the most popular use of a smart speaker?

What is the least popular use?

Solution: a.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

b.

c. The most popular use is “Listening to music” (74%). The least popular is a tie between “Using a kitchen assistant” and “Making phone calls” (24%).

18. Age and Ridesharing. A Gallup Poll showed that 30% of all Americans regularly use a ridesharing service such as Lyft or Uber. The file rideshare contains the survey results by age category. LO 1, 2, 4 a. Construct a column chart that shows the percentage of respondents who use a ride share by age category. Use “Who Uses Rideshare?” as the chart title and “Age (years)” as the horizontal axis title. Edit the chart to make it easier to interpret. Add data labels. b. Comment on the results.

Age

Percentage who use Rideshare

18-29

45%

30-49

36%

50-64

23%

65+

13%

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: a.

b. The column chart confirms what our intuition likely suggests. Older age categories use rideshare less than younger age categories.

19. Exploring Private Colleges (Revisited). In this problem, we revisit the charts in Problem 11 showing the relationships between tuition and year founded, and graduation rate and year founded. The two charts are similar. Consider the data in the file colleges. The file contains the following data for the sample of 102 private colleges: year founded, tuition and fees (not including room and board), and the percentage of undergraduates who obtained their degree within six years (source: The World Almanac). LO 1, 2, 4 a. Create a scatter chart to explore the relationship between tuition and percent who graduate. Use “Graduation Rate versus Tuition” as the chart title, “Tuition” as the horizontal axis title, and “Graduation Rate (%)” as the vertical axis title. b. Comment on any apparent relationship.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: a.

b. As the scatter chart reveals, there is a positive correlation between the tuition a college charges and its graduation rate.

20. Top Management. The Drucker Institute ranks corporations for managerial effectiveness based on a composite score derived from the following five factors: customer satisfaction, employee engagement and development, innovation, financial strength, and social responsibility. The file managementtop25 contains the top 25 companies in the Institute’s ranking based on the composite score (source: The Wall Street Journal). For each company, the industry sector, the company name, and the composite score are given. LO 1, 2, 4 a. Create a treemap chart using these data with the sector being the category, company being the subcategory, and the composite score being the quantitative variable. Use “Management Top 25” for the chart title. Hint: Be sure to first sort the data by sector. b. In the sector with the most companies in this top 25, which company has the highest composite score?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: a.

b. Technology is the sector with the most companies in the Top 25 list. Out of these 12 companies, Amazon has the highest composite score.

21. Biodiversity Preservation. Ecologists often measure the biodiversity of a region by the number of distinct species that exist in the region. Nature reserves are lands specifically designated by the government to help maintain biodiversity. Care must be taken when setting up a network of nature reserves so that the maximum number of species can exist in the network. Geography matters as well, as putting reserves too close together might subject the entire network to risks, such as devastation from wildfires. The initial step in this type of planning usually involves mapping the number of species that exist in each region. The file species contains the number of unique species that exist in each of the 50 states in the United States. LO 1, 2, 4 a. Create a choropleth map that displays number of species by state. Use “Number of Species per State” for the chart title. Add data labels. b. Comment on the distribution of species over the United States. Which regions of the United States have relatively many species? Which regions have relatively few species? c. Which two states have the most species?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: a.

b. The southeast and the west regions have many species, the north central and northeast regions have relatively few species. c. California and Texas have the most species.

22. Disney Ticket Prices (Revisited). In this problem, we revisit Problem 10, which displays the price of a general admission ticket to Walt Disney World for the years 2000 to 2020.

However, these prices did not factor in inflation over these years. The file disneypricesadjusted gives the general admission price and the general admission price adjusted for inflation for the years 2000 to 2020. LO 1, 2, 4 a. Create a line chart that shows the price of admission and the adjusted price of admission for the years 2000 to 2020. b. Explain what the adjusted ticket price data series shows that the nominal ticket price data series did not.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: a.

b. The prices adjusted for inflation show historical ticket prices in 2020 dollars and therefore allow the audience to observe how much ticket prices increased above the price increases in goods across the U.S. economy.

23. Bubble Chart Labels. The following bubble chart shows TSA wait time (in minutes) on the horizontal axis, cheapest daily parking rate on the vertical axis, and the size of each bubble is the number of enplanements in a year (measured in millions). The file airportbubblechart contains this chart. LO 2, 4

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

a. Using the following steps, add labels to the bubbles so that the airport codes are easily identifiable with each bubble.

Step 1. Click anywhere on the chart Step 2. Click the Chart Elements button

and select Data Labels

This puts the value of enplanements in each bubble Step 3. Click the Chart Elements button

and move the cursor over Data Labels,

and then select the black triangle on the right down menu.

to open a drop-

From this drop-down menu, select Other Options to reveal the Format Data Labels task pane Step 4. When the Format Data Labels task pane appears, under Label Contains, select Value from Cells and click the Select Range…button When the Data Label Range dialog box opens, select cells A2:A16 in the worksheet Click OK Step 5. In the Format Data Labels task pane, deselect Y Value under Label Contains b. Which airport has the lowest TSA wait time? c. Which airport has the most enplanements?

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22

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: a.

b. The airport with the lowest TSA wait time is BNA. c. The airport with the most enplanements is the one with the largest bubble: ATL. 24. Regional Gains and Losses in Population. The U.S. Census Bureau tracks shifts in population by each state and region in the United States. The net migration rate is an indicator of the movement of people from one area to another. A positive net migration rate means more people moved to the area than moved away, and a negative net migration rate means more people left the area than moved to the area. Mathematically the net migration rate N is defined as follows:

N=

(I-E) 1000 M

Where I = number of people moving to the area in the year under consideration, E = the number of people moving away from the area in the year under consideration, and M = the mid-year population of the area. The file netmigration contains net migration rates for four regions of the United States. LO 1, 4 a. Create a heat map using conditional formatting with the Blue-White-Red Color Scale. b. Which regions are losing population? Which regions are gaining population?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

Solution: a.

b. The Northeast and Midwest regions are losing population whereas the South and West are gaining population.

25. Income Statement. An income statement is a summary of a company’s revenues and costs over a given period time. The data in the file bellevuebakery is an example of an income statement. It contains the revenues and costs for last year for Bellevue Bakery.

Revenues include gross sales and other income. Costs include returns, cost of goods sold, advertising, salaries/wages, other operating expenses, and taxes. In the income statement there are intermediate calculations: Net Sales = Gross Sales – Returns Gross Profit = Net Sales – Other Income – Cost of Goods Sold Net Income Before Taxes = Gross Profit – Advertising – Salaries/Wages – Other Operating Expenses Net Income = Net Income Before taxes – Taxes Create a waterfall chart of the income statement for Bellevue Bakery. Use “Bellevue Bakery Income Statement” for the chart title. Click the column associated with each of the calculations above and select Set as Total. Edit the chart to make it easier to interpret. LO 1, 2 Solution:

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

26. Marathon Records. The file marathonrecords contains marathon world records for ages from 6 to 90 for women and men (records for ages 9 and 10 are missing) LO 1, 2, 4 a. Create a scatter chart with age on the horizontal axis and the women’s marathon record on the vertical axis. Use “Female Marathon Records (minutes)” as the vertical axis title and “Age (years)” as the horizontal axis title. Edit the chart to improve interpretation. b. Create a scatter chart with age on the horizontal axis and the men’s marathon record on the vertical axis. Use “Male Marathon Records (in minutes)” as the vertical axis title and “Age (years)” as the horizontal axis title. Edit the chart to improve interpretation. c. Create a scatter chart that plots both the women’s record versus age and the men’s record versus age. Select Scatter with Straight Lines. Use “Marathon Records (minutes)” as the vertical axis title and “Age (years)” as the horizontal axis title. Edit the chart to improve interpretation. d. Based on the charts in parts a, b, and c, what observations can you make regarding the women’s and men’s marathon records?

Solution: a.

b.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 2: Selecting a Chart Type

c.

d. The female and male data follow the same pattern. As expected, younger and older ages have slower record times. The fastest records for both females and males are generally between the ages of 20 and 40. Male records are faster for a given age with a few exceptions at earlier ages.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 3: DATA VISUALIZATION AND DESIGN

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1 CONCEPTUAL ............................................................................................................................. 1 APPLICATIONS.......................................................................................................................... 13

END OF SECTION PROBLEM SOLUTIONS CONCEPTUAL 1.

Memory Used for Preattentive Attributes. Which of the following types of memory is used to process preattentive attributes? LO 1 i. Iconic memory ii. Short-term memory iii. Long-term memory iv. Random access memory Solution: i.

2. Preattentive Attributes in a Data Visualization. Which of the following statements about the use of preattentive attributes in a data visualization are true? (Select all that apply.) LO 1 i. The use of preattentive attributes reduces the cognitive load required by the audience to interpret the information conveyed by a data visualization. ii. Preattentive attributes can be used to draw the audience’s attention to certain parts of a data visualization. iii. Overuse of preattentive attributes can lead to clutter and can be distracting to the audience. iv. Preattentive attributes include attributes such as proximity and enclosure.

Solution: i., ii., and iii 3. Descriptions of Gestalt Principles. For each description below, provide the name of the Gestalt principle that is being described. LO 2 a. Objects that are physically close to one another are seen as belonging to the same group. b. Objects that are linked in some way are seen as belonging to the same group. c. Objects that are physically bound together are seen as belonging to the same group.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

d. Objects with like characteristics such as color, shape, size, etc. are seen as belonging to the same group.

Solution: a. Proximity, b. Connection, c. Enclosure and d. Similarity 4. Scatter with Straight Lines and Markers Chart in Excel. Using a Scatter with Straight Lines and Markers Chart in Excel makes use of which Gestalt principle? LO 2 i. Similarity ii. Proximity iii. Enclosure iv. Connection Solution: iv.

5. Increasing the Data-Ink Ratio on a Chart. Which of the following changes to a chart would increase the data-ink ratio? (Select all that apply.) LO 3 i. Removing unnecessary gridlines. ii. Removing a legend on a bar chart where each bar is already labeled with the same information. iii. Adding axes labels to a chart where the units used in each axis are not clear from the chart title. iv. Adding data labels for each point on a scatter chart when the audience does not need to know exact values.

Solution: i., ii., and iii.

6. Pie Charts versus Bar or Column Charts. Which of the following reasons accurately describe why bar or column charts are often preferred to pie charts for a data visualization? (Select all that apply.) LO 4 i. Bar and column charts utilize the Gestalt principle of proximity while pie charts use the Gestalt principle of connection. ii. Using a legend for a pie chart creates unnecessary eye travel that can often be reduced by using a bar or column chart that does not require a legend. iii. Bar and column charts use length rather than size to make comparisons, and length is much easier for the audience to interpret than size. iv. Pie charts often use different colors to differentiate each piece of the pie that can create unnecessary clutter compared to bar or column charts that can display the same information without the use of multiple colors.

Solution: ii., iii., and iv.

7. Market Segmentation for Brandience. Brandience Marketing LLC provides marketing analytics consulting for clients. For one of its clients, Brandience has been asked to perform a market segmentation study for a business client that provides auditing services to manufacturing customers. The client believes there are two variables of importance that should be used to group similar customers into clusters: Years of Service with the Client and Total Assets. Brandience plans to use a clustering algorithm to group similar customers into different clusters, but before applying the algorithm, Brandience creates a simple scatter chart to plot each customer based on their Years of Service with the Client and Total Assets. The scatter chart created by Brandience follows. LO 2

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

a. Based on the Gestalt principle of proximity, how many different groups of customers are shown in the scatter chart? b. What other Gestalt principle could be used to reinforce the appearance of the different groups of customers for the audience?

Solution: a. Based on the principle of proximity, there appears to be three distinct groups of customers. One group has relatively low Total Assets and Years of Service; another group has relatively low Total Assets but high Years of Service; and another group has high Total Assets and Years of Service. b. The Gestalt principle of enclosure could be used to emphasize these three different groups in the scatter chart. (See solution to Problem 17 for an updated chart.)

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

8. Philadelphia City Schools. The following chart displays data related to the student enrollment at several schools located in the Philadelphia City School District. LO 1, 4

a. Which preattentive attributes are being used in this chart? b. What changes would you suggest to this chart to make it easier for the audience to interpret?

Solution: a. The pie chart uses the preattentive attributes of size and color to differentiate between the enrollments. Because size is difficult for people to compare, it is difficult to tell how much larger the enrollments of some schools are than others. The use of color here is also overwhelming and distracting. b. This chart would be better displayed as a sorted bar (or column) chart that uses length rather than size to make relative comparisons. Using a sorted bar (or column) would also remove the need for using color to differentiate among the schools. It would be less distracting and would require less eye travel than this pie chart where the audience must match up the school name from the legend with the appropriate piece of the pie.

9. Percentage of College Graduates and Median Monthly Rent in New York City. The following scatter chart shows the relationship between the percentage of college graduates and the median monthly rent in different sub-boroughs (a description of an area within the city) of New York City. Each point in the scatter chart represents a different sub-borough in New York City. LO 1

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

College Graduates (%) 100

80

60

40

20

0 0

500

1,000

1,500

2,000

2,500

Median Monthly Rent ($)

a. Which preattentive attribute is used in this scatter chart? b. What can you say about the relationship between the percentage of college graduates and the median monthly rent in sub-boroughs of New York City?

Solution: This scatter chart uses the preattentive attribute of spatial positioning to show the relative percentage of college graduates and median monthly rent of different subboroughs in New York City.

The higher the point corresponding to a sub-borough is placed vertically on the chart, the higher the percentage of college graduates within that sub-borough. The further right horizontally the point corresponding to a sub-borough is placed on the chart, the higher the median monthly rent is in that sub-borough. This chart tells us that as median monthly rent increases, the percentage of college graduates increases.

10. Patient Waiting Times at Scott & White. The Scott & White Medical Center in Temple, Texas, is examining the mean waiting time for patients to receive common orthopedic surgeries at its facility. The medical administrators have collected data on patient waiting times. The mean patient waiting times (in days) for different orthopedic surgeries are shown in the chart below. The medical center is particularly interested in the wait times for anterior cruciate ligament (ACL) reconstruction surgeries because ACL reconstructions are the most common type of orthopedic surgery performed at its facility. LO 1

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

What types of preattentive attributes are used in this chart and what information do these attributes convey to the audience?

Solution: The bar chart uses the preattentive attribute of length to make it easy to compare the mean patient wait time for each type of surgery. It is easy to determine that Ankle Repairs have the longest patient wait time and Shoulder Arthroscopies have the shortest wait time. The chart also uses the preattentive attribute of color to direct the reader’s attention to the mean patient wait time for ACL Reconstruction since this type of surgery is of special interest to medical administrators.

11. Comparing Managing Consultants at Platt Consulting. Platt Consulting Services is interested in comparing the number of customer accounts managed by its consultants. In particular, the company needs to compare the number of accounts managed by Bernie Smith, Stanley Lucas, and Gracie Rogers because these three accountants started with the company at approximately the same time and have similar skills. The chart below is a default chart produced in Excel. LO 1

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

a. Which preattentive attributes are used in the pie chart? b. What preattentive attributes would you use in redesigning this chart to improve its clarity for the audience?

Solution: a. The pie chart uses the preattentive attributes of shape and color. However, the use of shape is ineffective because it is difficult to compare the relative sizes of the pieces of the pie to determine which managers are handling the greatest number of customer accounts. The use of a different color for each piece of the pie in the chart is also overwhelming and ineffective. b. A bar chart uses length to compare the number of customer accounts management, so would likely be a much better data visualization choice here. Because we are most interested in comparing Bernie Smith, Stanley Lucas, and Gracie Rogers, it would make more sense to use one color for these three bars and a different color for the other bars to make the comparison easy for the audience. (See solution to Problem 17 for an example chart.)

12. Basketball Scouting Report. Meg Lawson is an assistant coach for a high school basketball team. Meg has prepared a scouting report on her team’s upcoming opponent, which is led by a star player who prefers to shoot from near the 3-point line. Meg has created the following diagram to show this star player’s shot selection from a recent game. Each × corresponds to a missed shot and each ⚫ corresponds to a made shot. Meg has noticed that the star player made most of her shots from the area on the court located at the top of the 3-point line while missing most of her shots from the corners. Meg wants to draw her team’s attention to these areas so that they can properly defend against this star player. LO 1, 2

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

a. What preattentive attributes and Gestalt principles has Meg used in this diagram? b. Are the preattentive attributes and Gestalt principles used in this diagram effective in communicating Meg’s message to her audience? Why or why not?

Solution: a. The diagram uses the preattentive attributes of shape and spatial positioning. The diagram differentiates between made and missed shots using different shapes, and it uses spatial positioning to communicate the positions on the court from which the star player took her shots. It is very helpful that the diagram includes the markings of an actual basketball court to indicate this spatial positioning in a frame of reference that should be familiar to Meg’s team. The diagram also uses the Gestalt principles of similarity, proximity, and enclosure. Meg has used a common symbol to indicate made shots so the audience groups these together, and a different common symbol to indicate missed shots so the audience easily groups these together. Meg has also used dashed lines to enclose groups of shots taken by the star player that are in close proximity in three different areas of the court: at the top of the 3-point line and in each corner. This could correspond to the star player’s preferred areas from which to shoot. b. The diagram is effective at indicating from where the star player likes to take shots and also where she tends to make a higher percentage of her shots. It should be noted that these data are only for a single game, and we do not know what type of defense the opposing team was playing against the star player when these data were collected.

However, this diagram is likely still useful for helping Meg’s team prepare a defensive plan against this player.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

13. Revenues and Costs at a Manufacturing Firm. A manufacturing firm would like to compare its monthly revenues and costs for the previous year. The following table shows the revenues and costs for the company in each month of the previous year. Of particular interest to the company is how the company’s revenues and costs perform during the summer months because that is when the company’s sales tend to be highest. LO 3 Month

Revenues ($1,000s)

Costs ($1,000s)

Jan

1,121

1,007

Feb

997

1,002

Mar

1,151

1,010

Apr

1,202

1,085

May

1,422

1,287

Jun

1,877

1,488

Jul

1,911

1,621

Aug

1,988

1,625

Sep

1,521

1,617

Oct

1,288

1,178

Nov

1,100

1,008

Dec

1,022

987

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

a. Compare the two charts above (Chart A and Chart B). Which chart has the higher dataink ratio? Why? b. How does the chart with the higher data-ink ratio help the audience interpret the chart more effectively?

Solution: a. Chart B has the higher data-ink ratio. The ink used in Chart B is more relevant to emphasizing what is important to the audience in the chart. b. In Chart A, the gridlines serve no useful purpose. The horizontal and vertical axes titles in Chart A are also redundant and do not convey unique useful information. However, Chart A is missing important information on the scale of the vertical axis – the revenues and costs are shown in $1,000s. Chart A labels each month on the horizontal axis, but it does not clearly define the summer season. Because summer is the most important season to label for this chart, Chart B includes a better use of ink to label the summer season.

14. Serif versus Sans-Serif Fonts. Consider the fonts that are shown in the table that follows. LO 5 (1) (2) (3)

Abcd123 Abcd123 Abcd123

(4) A b c d 1 2 3 (5) A b c d 1 2 3 (6) A b c d 1 2 3

(7) A b c d 1 2 3 (8) A b c d 1 2 3 (9) A b c d 1 2 3

a. Which of these fonts are considered serif fonts? b. If you are creating text for a data visualization that will mostly be viewed on smartphones and other small mobile devices, would you suggest using the serif fonts for text in the data visualization? Why or why not?

Solution: a. Fonts (3), (4), (6), and (7) are serif fonts because the characters contain serifs. b. Sans serif fonts are preferred to serif fonts for data visualizations viewed on smartphones and small mobile devices. This is because sans serif fonts are generally better for text displayed digitally and for text displayed at small sizes.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

15. Approval Voting Results. Approval voting is a type of voting system in which voters can vote for any number of eligible candidates. A vote for a candidate in this type of system indicates that the voter “approves” of that candidate for the position the candidate is seeking. In the final tally of the election results, the total number of approval votes for each candidate is calculated. The candidate who receives the most approval votes is declared the winner. The figure below displays the results from an approval voting election in which there were four eligible candidates: C. Sittenfeld, A. Marshall, S. Keskin, and K. Nowak. A total of 1218 voters participated in this election. The table below shows the number of votes received by each candidate as well as the proportion of voters who approved of each candidate. LO 4, 6 Candidate C. Sittenfeld A. Marshall S. Keskin K. Nowak

Number of Votes Received 482 689 354 514

Proportion of Voters Who Approve of This Candidate 39.6% 56.6% 29.1% 42.2%

a. The figure displays the election result proportions as a 3D pie chart. What problems are associated with displaying the election results in this way? b. Suggest an alternative type of chart for displaying these data that would be easier for the audience to interpret. Explain why this alternative type of chart would be easier to interpret.

Solution: a. Because the percentages do not add up to 100%, a pie chart is not an effective way to display this information. Furthermore, the third dimension in this 3D pie chart does not convey any meaningful information, so it only adds clutter. The pie chart also requires considerable eye travel because the audience must match the name of each candidate with the appropriate color in the pie. b. A 2D bar or column chart would be better to display these data. Bar and column charts use length rather than area to communicate insights to the audience, so they are easier to interpret. A bar or column chart also removes the need for a legend,

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

which reduces eye travel as well as the need for different colors and simplifies the chart. Finally, a bar or column chart can also be sorted to make it even easier for the audience to interpret the results of the election.

16. Headcount and Annual Revenues at BeFit Gyms. BeFit Gyms operates four exercise gyms in the state of Michigan. The gyms are located in Saline, Tecumseh, Dexter, and Jackson.

The gyms are different sizes, and they require different headcounts of staff to operate.

The table below displays the headcount, in full-time equivalent (FTE) employees and annual revenue ($1,000s) for each of the four locations. LO 4, 6 Gym Location Saline Tecumseh Dexter Jackson

Headcount (FTE)

Annual Revenue ($1,000s)

18 11 9 12

787 674 784 642

a. The clustered column chart displays the headcount and annual revenue for each location. What are the problems with displaying these data using this type of chart? b. Would it be appropriate to display these data using a stacked column chart rather than a clustered column chart?

Solution: a. The units for headcount (FTE) are different from the units for annual revenue ($1,000s), so it is not clear what the vertical axis in this graph represents. Because the scale of headcount is also very different from annual revenue, it is difficult to see the columns corresponding to headcount in this chart, and it is nearly impossible to make relative comparisons among these columns. b. Because the two variables shown in this chart represent different units (FTE for Headcount and $1,000s for Annual Revenue), it would not be appropriate to combine them for a stacked column chart.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

APPLICATIONS 17. Comparing Managing Consultants at Platt Consulting (Revisited). In this problem, we revisit the pie chart in Problem 11. Platt Consulting Services is interested in comparing the number of customer accounts managed by its managing consultants. In particular, the company needs to compare the number of accounts managed by Bernie Smith, Stanley Lucas, and Gracie Rogers because these three accountants started with the company at about the same time and have similar skill sets. The following chart is a default chart produced in Microsoft Excel. LO 1, 6

Use the data in the file plattconsulting to create a new data visualization that uses a different type of chart and proper use of preattentive attributes to allow for easier comparison of the number of accounts managed by each consultant.

Solution: Instead of a pie chart that relies on the preattentive attribute of size, we choose a bar chart because it uses the preattentive attribute of length. This makes it much easier to compare the relative number of customer accounts managed by each manager. We also use the preattentive attribute of color to differentiate the managers Bernie Smith, Gracie Rogers, and Stanley Lucas to make it easier to compare these three managers against one another.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

18. Market Segmentation for Brandience (Revisited). In this problem, we revisit the scatter chart in Problem 7. Starting with the chart in the file brandience_chart, modify the chart by using an additional Gestalt principle to make it more obvious to the audience which clients are in each cluster. Which additional Gestalt principle did you use? LO 2, 4 Solution:

Market Segmentation Analysis of Brandience Clients Total Assets ($ millions) 30

25

20

15

10

5

0 0

2

4

6

8

10

12

Years of Service

The modified chart also uses the Gestalt principle of enclosure.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

19. Comparing Direct and Indirect Costs at Sackenheim Compressors. Sackenheim Compressors, Inc. manufactures air compressors for industrial use. The company is performing an analysis of its direct and indirect costs related to manufacturing a particular type of air compressor. It has gathered cost data for the previous 20 weeks, and it would like to identify any trends in the data. A scatter chart created using the data follows. LO 2, 4

a. Which Gestalt principle should be used here to make it easier for the audience to identify trends in the data? b. Using the chart included in the file sackenheim_chart as a starting point, create an improved version of this chart by applying the Gestalt principle from part a that makes any trends in the data more obvious to the audience.

Solution: a. The Gestalt principle of connectedness should be applied separately to the series of data points for direct and indirect costs. This will make any trends in the data more obvious to the audience. b. The chart below uses the Gestalt principle of connectedness to make trends more obvious to the user. This chart does not include the individual markers at each data point, but this is mainly a matter of preference, and these can be retained if preferred.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

20. Sales Performance Bonuses. A sales manager is trying to determine appropriate sales performance bonuses for her team this year. The following table contains the data relevant to determining the bonuses, but it is not easy to read and interpret. Reformat the table using the data in the file salesbonuses to improve readability and to help the sales manager make her decisions about bonuses. (Hint: It will also help the sales manager if the table is ordered from top-to-bottom by Total Sales.) LO 3

Salesperson Smith, Michael

Total Sales ($) 325000.78

Average Performance Bonus Previous Years ($) 12499.3452

Customer Accounts 124

Years with Company 14

Yu, Joe

13678.21

239.9434

9

7

Reeves, Bill

452359.19

21987.2462

175

21

Hamilton, Joshua

87423.91

7642.9011

28

3

Harper, Derek

87654.21

1250.1393

21

4

Quinn, Dorothy

234091.39

14567.9833

48

9

Graves, Lorrie

379401.94

27981.4432

121

12

Sun, Yi

31733.59

672.9111

7

1

Thompson, Nicole

127845.22

13322.9713

17

3

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16

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

Solution: Total Sales ($) 452,359

Average Performance Bonus Previous Years ($) 21,987

Customer Accounts 175

Years with Company 21

Graves, Lorrie

379,402

27,981

121

12

Smith, Michael

325,001

12,499

124

14

Quinn, Dorothy

234,091

14,568

48

9

Thompson, Nicole

127,845

13,323

17

3

Harper, Derek

87,654

1,250

21

4

Hamilton, Joshua

87,424

7,643

28

3

Salesperson Reeves, Bill

Sun, Yi

31,734

673

7

1

Yu, Joe

13,678

240

9

7

The readability of the table has been improved by removing unnecessary gridlines, leftaligning the first column because it contains text entries, right-aligning all other columns because they contain numerical values, and sorting the table to put the largest values of Total Sales ($) at the top of the table.

21. Gross Domestic Product Values over Time. The following table shows an example of gross domestic product values for five countries over six years in equivalent U.S. dollars ($). LO 3 Gross Domestic Product (US $) Country

Year 1

Year 2

Year 3

Year 4

Year 5

Year 6

Albania

7385937423

8105580293

9650128750

11592303225

10781921975

10569204154

Argentina

169725491092

198012474920

241037555661

301259040110

285070994754

339604450702

Australia

704453444387

758320889024

916931817944

982991358955

934168969952

1178776680167

Austria

272865358404

290682488352

336840690493

375777347214

344514388622

341440991770

Belgium

335571307765

355372712266

408482592257

451663134614

421433351959

416534140346

a. How could you improve the readability of this table? b. The file gdp_years contains sample data from Year 1 to Year 6 in us $. Create a table that provides all these data for an audience. Format the table to make it as easy to read as possible. Hint: It is generally not important for the audience to know GDP to an exact dollar figure. It is typical to present GDP values in millions or billions of dollars.

Solution: a. The readability of the table could be improved by removing unnecessary gridlines, left-aligning the first column because it contains text entries, right-aligning all other columns because they contain numerical values, reducing the number of digits displayed by displaying numerical values in millions or billions of dollars, and using shading to differentiate the columns. Note that we could also sort these values by GDP in the most recent year if this was the value of most interest.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

b.

Gross Domestic Product (US $ billions) Country

Year 1

Year 2

Year 3

Year 4

Year 5

Year 6

Albania

7.4

8.1

9.7

11.6

10.8

10.6

Argentina

169.7

198.0

241.0

301.3

285.1

339.6

Australia

704.5

708.3

916.9

983.0

934.2

1178.8

Austria

272.9

290.7

336.8

375.8

344.5

341.4

Belgium

335.6

355.4

408.5

451.7

421.4

416.5

Brazil

756.8

935.5

1175.0

1407.0

1370.8

1782.4

Canada

1056.8

1193.9

1332.1

1404.8

1245.2

1469.9

18.9

21.2

24.7

28.0

28.0

33.9

Costa Rica Czech Republic

111.7

128.7

156.6

194.6

170.9

172.6

Finland

169.9

180.2

214.8

236.6

206.7

207.9

France

1915.0

2015.0

2312.8

2541.6

2367.9

2301.8

Germany

2516.9

2632.8

2984.7

3258.9

2973.7

2966.1

Greece

217.2

234.3

273.8

307.1

292.6

269.1

Ireland

177.7

195.3

229.6

233.3

199.5

186.2

Israel

122.4

133.2

153.4

185.7

178.7

199.8

Italy

1597.3

1661.9

1892.7

2063.9

1900.0

1836.9

Mexico

823.3

928.5

1011.9

1085.6

858.3

1010.3

Netherlands

567.8

600.9

694.8

775.4

708.0

700.8

New Zealand

108.9

105.1

129.0

125.7

112.9

136.2

Peru

72.3

84.4

98.5

117.8

120.4

144.3

Poland

267.8

300.1

371.9

463.4

282.6

413.4

Portugal

165.3

172.9

200.1

218.7

206.0

200.5

Saudi Arabia

317.4

358.4

386.7

477.3

374.4

436.2

Singapore

119.7

139.1

167.0

179.3

173.8

209.7

South Africa

220.3

232.2

254.4

247.5

256.9

328.8

Spain

1012.0

1100.0

1293.2

1459.0

1361.0

1287.9

Switzerland

250.6

368.2

409.2

474.7

464.9

498.2

Turkey

425.5

467.9

579.0

656.6

557.7

655.8

United Kingdom

2030.3

2178.0

25.04.6

2381.9

1959.2

2005.6

United States

12,579.7

13,336.3

14,010.9

14,369.5

14,113.3

14601.6

22. Monthly Revenue Data at Tedstar, Inc. The following table provides monthly revenue values for Tedstar, Inc., a company that sells valves to large industrial firms. The monthly revenue data have been graphed using a line chart in the following figure. LO 3, 4 Month Revenue ($)

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

145,869

123,576

143,298

178,5050

186,850

192,850

134,500

145,286

154,285

148,523

139,600

148,235

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18

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

a. What characteristics of this line chart make it more difficult than necessary to interpret? b. Using the data in the file tedstar, create a new line chart for the monthly revenue data at Tedstar, Inc. Format the chart to make it easy to read and interpret. Use the chart title “Tedstar, Inc. Revenue Analysis” and the vertical-axis title “Monthly Revenue ($).”

Solution: a. The chart contains unnecessary gridlines, the vertical-axis label values are spaced much too close together, and the shading of the chart does not add value. b.

23. Comparing Hoxworth Blood Center Locations. Hoxworth Blood Center, located in Cincinnati, Ohio, is a leader in transfusion medicine. Founded in 1938, it is the second oldest blood bank in the United States. Hoxworth operates at seven locations in the Greater Cincinnati area where it collects blood from donors. Hoxworth is performing a comparison of the amount of blood donors serviced by each of its locations during the month of October.

Suppose that Hoxworth has a stated goal of each location servicing an average of 50 blood donors per day each month. The column chart that follows compares the average number of blood donors at each Hoxworth location. However, this chart is cluttered, and the data-ink

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19

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

ratio is low. Starting with the chart in the file hoxworth_chart, declutter the chart and improve the data-ink ratio to produce an improved column chart. LO 3, 4

Solution: There is a lot of redundant information in this chart that can be removed to declutter the chart. The grid lines, other than the goal of 50 donors, serve no useful purpose and can be removed. The legend of “Number of Donors Serviced” is redundant with both the chart title and the vertical axis title; therefore, we can also remove the chart legend. Finally, we can further improve the data-ink ratio by simplifying the vertical axis title and the label for the goal amount. In the chart shown below, we have also moved the vertical axis title location and rotated the text to reduce the amount of eye travel required by the audience.

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20

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

24. Comparing Package Delivery Drivers. Red Sky Delivery performs “last-mile” delivery services for online retailers such as Amazon. Red Sky employs delivery drivers who perform the “last-mile” of delivery service by delivering packages to individual residence and business locations. Red Sky measures several delivery driver performance metrics, including number of delivery stops completed per eight-hour shift. The table below provides data on nine Red Sky delivery drivers and their average number of packages delivered per shift over the previous 30 days. LO 1, 3, 4 Delivery Driver

Average Number of Delivery Stops Completed (per shift)

Amy Urbaczewski

92.87

Sally Melouk

110.78

Brenda Barnes

114.2

Jonathan Payne

132.5

Bruce Wheeler

148.2

Cam Madsen

87.51

Sheila Stevens

139.82

Grant Inhara

154.23

Finn Helton

109.11

a. Using the data in the file redsky_deliveries, create a column chart to display the information in the table above. Format the column chart to best display the data.

Use a chart title of “Comparing Red Sky Delivery Drivers,” and a vertical axis title of “Average number of deliveries per shift.” Get rid of any unnecessary gridlines and add data labels that show the average number of delivery stops completed for each driver. b. Create a sorted column chart to make it easier for the audience to see which drivers have the highest and lowest average number of delivery stops per shift. c. Further investigation by Red Sky indicates that all of these delivery drivers except Amy Urbaczewski have similar delivery routes. Amy typically delivers in more rural areas while all other drivers support more urban routes. Red Sky wants to draw attention to the fact that Amy’s routes are different than the others. Modify the sorted column chart by changing the color of the column associated with Amy Urbaczewski to indicate that this column is different from the others.

Solution: Note that we do not include vertical axes in the charts below because we use data labels on the columns. This makes the vertical axis redundant for these charts.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

a.

b.

c.

25. Inbound and Outbound Shipping Costs at Rainbow Camping. Rainbow Camping makes outdoor equipment for camping and backpacking that it sells online. Because Rainbow Camping mails each of its sales from its distribution center direct to the consumer, it spends considerable funds each month on outbound shipping. Rainbow Camping also has costs related to inbound shipping to get its products from the manufacturers to its

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22

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

distribution center. Rainbow Camping would like to examine its outbound and inbound shipping expenses over the last 12 months (labeled months 1 through 12). These shipping costs are shown in the following table. LO 4 Shipping Costs ($1,000s) Month

Outbound

Inbound

1

478

324

2

524

274

3

628

224

4

787

292

5

648

348

6

612

309

7

598

378

8

641

287

9

546

292

10

476

345

11

378

304

12

512

298

a. Using the data in the file rainbowcamping, a single chart that displays both the outbound and inbound shipping costs for each month on the same chart. Use the title “Rainbow Camping Shipping Costs Analysis” for the chart title, “Costs ($1,000s)” for the vertical-axis title and “Month” for the horizontal-axis title. Format the chart title and vertical axis title to make these easy for the audience to interpret. Modify the Minimum and Maximum Bounds of the horizontal axis so that this axis starts at 1 and ends at 12 (Minimum and Maximum Bounds can be found in the Format Axis task pane by clicking on the Axis Options icon and then under Axis Options.) Remove the markers so that only lines are displayed for each of these shipping costs. Delete any unnecessary gridlines in the chart. b. To further minimize the eye travel required by the audience, delete the default legend created with the chart and use text boxes to label the lines in the chart as “Outbound” and “Inbound”.

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23

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

Solution: a.

b.

26. University of Michigan Enrollments over Time. The University of Michigan was founded in 1817 as the first university in what was then the Northwest Territories of the United States. The university’s nickname is the Wolverines and its main campus is located in Ann Arbor, Michigan. The file michiganenrollment contains enrollment data for students at the University of Michigan’s Ann Arbor campus for Fall Semesters from 1966 to 2016 in fiveyear increments. Create a default chart for these data by clicking Insert in the Ribbon in Excel and then choosing Scatter with Straight Lines and Markers from the Charts group. Use the principles of data-ink ratio and decluttering to improve this chart for the audience. LO 3, 4 In particular, you should: • Create meaningful chart and vertical axis title, and position them appropriately to minimize eye travel.

• Adjust the Minimum and Maximum Bounds of the horizontal axis to make it clear to the audience that the data points correspond to 1966, 1971, 1976, etc. (Minimum and Maximum Bounds can be found in the Format Axis task pane by clicking on the Axis • • •

Options icon and then under Axis Options.)

Create an appropriate horizontal-axis title to ensure that the audience understands that these values correspond to Fall Semester enrollments and position this axis title to minimize eye travel.

Remove the gridlines and adjust the vertical axis units to increase the data-ink ratio.

Make any other improvements to the chart that you think would help the audience interpret this chart.

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24

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

Solution: To improve this chart we have made several changes. a. We have given the chart the title Comparing University of Michigan Enrollments in Five-Year Increments,” and we have used “Ann Arbor Campus Enrollment” for the vertical-axis title. Other titles could be chosen here so long as they convey the meaningful information to the audience. We have also left-justified the chart title and vertical-axis title, and we have moved them to line up with the vertical axis labels to minimize eye travel. b. We have set the Minimum Bound to 1966 and the Maximum Bound to 2016 by double clicking on the horizontal axis and then adjusting these values in the Format Axis task pane. By leaving the Major Units to 5.0, this then inserts the correct labels for each marker displayed on the chart. c. We have created the title “Fall Semester Year” for the horizontal axis to make it clear to the audience that these values correspond to Fall Semester Enrollments for the years displayed and we moved this axis title to near the end of the horizontal axis to minimize eye travel. d. We have removed the grid lines and changed the vertical axis units to display units of 10,000 to increase the data-ink ratio. e. Other possible improvements to the chart depend on the needs of the audience. If the audience needs to know exact enrollment values in each year, then we could add data labels to each marker to show the enrollment value corresponding to that marker. The color and size of the marker and line in the chart can also be adjusted to make the chart more visually appealing to the audience.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

27. Evaluating Marketing Strategies. Cuero Marketing Services (CMS) is a marketing agency that designs marketing plans for companies. CMS is working with a large global corporation on new brand strategies. CMS formed seven different test groups to evaluate how people perceive two competing ideas for new brand strategies. Each test group is composed of 25 people. CMS collects all data from the test groups, and for each member of the test group it creates an overall evaluation of whether the test group member has an overall good impression of the brand strategy or does not have an overall good impression of the brand strategy. To preserve confidentiality, CMS refers to the two competing brand strategies in all written documents as “Blue Triangle” and “Orange Square.” The table below shows how many test group members from each test group had an overall good impression of the Blue Triangle and Orange Square brand strategies. CMS would like to create a simple data visualization to show these data. LO 4, 6 Number of Positive Impressions Test Group Number

Blue Triangle

Orange Square

1

17

12

2

21

15

3

16

13

4

19

14

5

23

17

6

26

18

7

20

16

a. Using the data in the file cms, create a scatter chart that shows both data series in a single chart. Use the test group number on the horizontal axis and the number of test group members who had an overall good impression on the vertical axis. Use “Test Group Analysis for Brand Strategies” as the chart title, “Number of Members with Overall Good Impression of Strategy (out of 25)” as the vertical-axis title, and “Test Group” as the horizontal-axis title. Format the title to minimize eye travel and remove any unnecessary gridlines. b. To make the chart more intuitive for the audience, CMS would like to display markers that match the name of each brand strategy. To do this, remove the default legend from chart and replace the markers for the Blue Triangle brand strategy with blue triangles and use orange squares for the markers of the Orange Square brand strategy.

(Hint: The markers on a chart can be changed in the Format Data Series task pane by clicking on the Fill & Line icon , clicking on Marker, then Marker Options and selecting a marker shape from Built-in.) c. Change the type of chart used to display these data to a clustered column chart. Do you think the scatter chart, or the clustered column chart would be most effective for displaying these results to an audience? Why?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

Solution: a.

b.

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27

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

c.

The clustered column chart makes it easier to compare the results from within each test group. And most audiences would be more familiar with using a clustered column chart to perform a comparison such as this one. However, the scatter chart makes it obvious that the Blue Triangle brand strategy is preferred in six of the seven test groups. The scatter chart also allows for the use of the blue triangle and orange square markers in the chart. In most cases, either of these charts could be used to communicate the results from the test groups. If the audience is most interested in comparing the results within each test group, the clustered column chart could be preferred, but if the audience is more interested in which brand strategy performed best across test groups, then the scatter chart may be preferred.

28. Affinity and Capacity of Donors for Malaria No More. Nonprofits often score potential donors on multiple dimensions including affinity and capacity. Affinity attempts to measure how passionate and engaged the potential donor is regarding the nonprofit’s cause.

Capacity attempts to measure the donor’s available wealth and ability to donate to the nonprofit. Malaria No More is a nonprofit that focuses on eradicating malaria across the world. Suppose that Malaria No More measures the affinity and capacity of potential donors on scales of 1-100 where 1 corresponds to very little affinity or capacity and 100 corresponds to extreme affinity or capacity. The file malaria_chart contains a scatter chart showing a sample of 50 potential donors to Malaria No More including their affinity and capacity scores. LO 2, 4 a. Starting with the scatter chart in the file malaria_chart, improve the design of this chart to increase its effectiveness. Change the title of this chart to “Evaluating Potential Donors for Malaria No More.” Add a vertical axis title of “Capacity Score” and a horizontal axis title of “Affinity Score.” Format the chart title and axes titles to minimize eye travel. b. Malaria No More would like to improve this chart to convey a specific message to its audience. It wants to focus the audience’s attention on those potential donors with capacity and affinity scores greater than or equal to 80 because it believes that these

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

are the best donor prospects. Use the Gestalt principle of enclosure to highlight the potential donors on the chart. (Hint: To create an enclosure in Excel, click Insert on

the Ribbon, then click Shapes

in the Illustrations group.)

Solution: a.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

b.

29. Funstate Carnivals Staffing Analysis. Funstate Carnivals operates four large amusement parks, each of which is located in California. Funstate would like to examine the staffing across these four amusement parks. It is most interested in comparing the total number of staff employed at each park, but it is also interested in comparing the gender breakdown of the staffing at each park. The table below shows the total number of staff employed at each park, broken out by gender. LO 4 Total Number of Staff Location

Male

Female

Fresno

72

84

Sacramento

89

61

Long Beach

65

84

Oakland

48

51

a. Using the data in the file funstate, create a stacked bar chart to display these data.

Use different colors for Male and Female. Use the chart title, “Funstate Carnivals Staffing Analysis,” choose appropriate axes titles, and include a chart legend to identify Male versus Female in the bar chart. Format the chart to minimize eye travel and remove any unnecessary gridlines to increase the data-ink ratio. b. Funstate would like to show the exact numbers of Male and Female staff at each location on the chart. Add data labels to the stacked bar chart to display the number of Male and number of Female staff at each location. Format the data labels so they are easy for the audience to read.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

c. Because of decreased revenues, Funstate wants to implement a policy of no more than 125 total staff members at each location. Draw a line and use a text box to indicate “Staffing Goal = 125” on the stacked bar chart to show this limit. (Hint: Click

Insert on the Ribbon, then click Shapes in the Illustrations group to add a line and text box.) Which locations currently exceed this staffing limit?

Solution: a.

b.

Note that we have used white font for the data labels here to make them contrast with the colored bars. © 2025 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

c.

Long Beach, Sacramento and Fresno are all currently exceeding the staffing goal of 125.

30. Approval Voting Results (Revisited). In this problem, we revisit the data from Problem 15 on the results of an election using approval voting. The original figure in Problem 15 used a pie chart to display the results from an approval voting election in which there were four eligible candidates: C. Sittenfeld, R. Manley, S. Keskin, and K. Nowak. A total of 1218 voters participated in this election. LO 3, 4 a. Using the data in the file approvalvoting, create a sorted bar chart that displays the proportion of voters who approve of the candidate for each candidate. Choose appropriate titles for the chart and axes. Sort the bars so that the candidate who received the most votes is at the top. Use data labels to display the proportion of votes received by each candidate. Format the chart title to minimize eye travel and remove any unnecessary gridlines to increase the data-ink ratio. Which candidate should be declared the winner of this election? b. Create a sorted bar chart that displays the number of votes received by each candidate. Choose appropriate titles for the chart and axes. Sort the bars so that the candidate who received the most votes is at the top. Use data labels to display the number of votes received by each candidate. Format the chart title to minimize eye travel and remove any unnecessary gridlines to increase the data-ink ratio. Which candidate should be declared the winner of this election?

C. Do you think the sorted bar chart in part a or in part b is more effective for communicating the results of the election to an audience? Why?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

Solution: a.

(Note that we have not included a horizontal axis or horizontal axis labels since this information is included in the data labels and the chart title.)

Marshall should be declared the winner. b.

(Note that we have not included a horizontal axis or horizontal axis labels since this information is included in the data labels and the chart title.)

Marshall should be declared the winner. c. The sorted bar chart in part b is more effective. People expect percentages to add to 100%, so the sorted bar chart in part a can be confusing for the audience. The bar charts in parts a and b are nearly identical, but it should cause less confusion to show the total approval votes received rather than the proportion of voters approving of the candidate.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

31. Headcount and Annual Revenues at BeFit Gyms (Revisited). In this problem, we revisit the data from Problem 16 on staff headcount and annual revenues for BeFit Gyms. Recall that each gym is a different size. To support larger headcounts, larger gyms are expected to generate greater annual revenue. BeFit is interested in identifying the incremental revenue a location should expect from a larger headcount. In Problem 16, a clustered column chart was used to display these data. However, we would like to make it easier for the audience to make comparisons from these data and generate insights about the relation between headcount and annual revenue. LO 3, 4, 6 a. Using the data in the file befit, create two different column charts to display the headcount and annual revenue data for BeFit Gyms: one chart that displays the headcount for each location and one chart that displays the annual revenue for each location. Make sure to create a meaningful chart title for each chart and create vertical axes titles that clearly define the units of measurement. Remove unnecessary and redundant information to increase the data-ink ratio. Why might these two charts be easier for the audience to generate insights from the data than the original clustered column chart in Problem 16? b. Recall that the audience is most interested in identifying the incremental revenue a location should expect from a larger headcount. Create a single column chart using these data that would compare each location based on both headcount and annual revenue. (Hint: You can create a new metric for each location that measures the annual revenue per FTE.) Which location generates the greatest annual revenue per headcount?

Solution: a.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 3: Data Visualization and Design

Dividing the data into two different column charts allows us to label each vertical axis to make it clear to the audience what units are represented on the chart, and we can now easily compare the headcounts among locations because the vertical axes of the two charts have different maximum values. However, it is difficult to compare headcount and annual revenue at the same time among locations because these are now on different charts. b. We first create a new column in our data for Annual Revenue per FTE by dividing the annual revenue at each location by the headcount at each location as shown in the table below.

Gym Location Saline Tecumseh Dexter Jackson

Headcount (in FTE)

Annual Revenue ($1,000s)

Annual Revenue per FTE ($1,000s)

18 11 9 12

787 674 784 642

43.72 61.27 87.11 53.50

From these data, we can create a single column chart that uses annual revenue per FTE for each location as shown below.

We can now see that the Dexter location is generating the greatest annual revenue per headcount as measured by FTE. Note that we could also sort this chart by Revenue per FTE to make it easier to see which locations have highest and lowest annual revenue per FTE.

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35

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 4: PURPOSEFUL USE OF COLOR

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1 CONCEPTUAL ............................................................................................................................. 1 APPLICATIONS.......................................................................................................................... 14

END OF SECTION PROBLEM SOLUTIONS CONCEPTUAL 1.

Understanding Hue, Saturation, and Luminance. For each of the following statements, indicate whether hue, saturation, or luminance is being described. LO 1 a. The amount of gray in a color b. The position the light occupies on the visible light spectrum c. The intensity or purity of a color d. The relative degree of black or white in the color Solution: a. Saturation b. Hue c. Saturation d. Luminance

2. Differentiating Between Hue, Saturation, and Luminance. Each of the following pairs of colors differ on a single characteristic of color (hue, saturation, or luminance). Each pair of shapes provided in parts a through f is also provided in worksheets of the same names (a, b, c, d, e, and f) in the file huesatlum_chart. Use this file and the Colors dialog box to determine whether each pair of colors differs on hue, saturation, or luminance and explain your answer. LO 1

a. b. c. d.

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1

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

e. f.

Solution: a. Saturation − these colors differ on the amount of gray/intensity or purity of the hue in the color

b. Luminance − these colors differ on the relative degree of black or white

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

c. Luminance − these colors differ on the relative degree of black or white

d. Hue − these colors differ on their base color

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

e. Saturation − these colors differ on the amount of gray/intensity or purity of the hue in the color

f.

Luminance − these colors differ on the relative degree of black or white

3. Using Hue, Saturation, and Luminance to Differentiate Categories. The charts in parts a, b, and c each show 2019 and 2020 quarter 1 sales for nine popular midsize sedans. These charts are included in worksheets of the same names (a, b, and c) in the file q1sales_chart.

Use the Colors dialog box to determine whether hue, saturation, or luminance is used to differentiate the Honda Accord from the other eight models in each chart. LO 1

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4

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

a.

b.

c.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

d. Which of the charts in parts a, b, and c is least effective in differentiating between the Honda Accord and the other models? Why? Solution: a. Luminance is used to differentiate the Honda Accord from the other eight models in this chart (Hue = 180 and Sat = 139 for all bars, but Lum = 200 for the Honda Accord bars and Lum = 103 for all other models’ bars). b. Hue is used to differentiate the Honda Accord from the other eight models in this chart (Sat = 139 and Lum = 103 for all bars, but Hue = 0 for the Honda Accord bars and Hue = 180 for all other models’ bars). c. Saturation is used to differentiate the Honda Accord from the other eight models in this chart (Hue = 180 and Lum = 103 for all bars, but Sat = 255 for the Honda Accord bars and Hue = 103 for all other models’ bars). d. The bar chart in c is least effective because the contrast between the Honda Accord bars and the bars corresponding to the other models created by differences in saturation is not as stark as in the charts in a and b.

4. Using Categorical Color Schemes, Sequential Color Schemes, and Diverging Color Schemes. Identify whether a categorical color scheme, a sequential color scheme, or a diverging color scheme should be applied in each of the following examples. In each instance, explain why this is the appropriate color scheme. LO 2 a. You have been given the following data on a popular regional product’s unit sales and net profit for several markets.

City Amarillo Ft. Worth El Paso Dallas Houston San Antonio Austin

Sales (units) 99,299 112,219 117,893 139,486 143,721 157,241 175,555

Net Profit $122,619 −$132,762 $169,500 −$136,332 $63,646 $115,632 $80,707

From these data, you have created the following bar chart to show the number of units sold by market. Now you want to add the information on net profit to the bars on this chart to show the profit or loss earned in each market.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

b. You have been given the following data on mean daily high temperature for a city and number of cups of hot chocolate a chain of coffee shops sold in that city by month.

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Mean Daily High Temperature in Fahrenheit 27 32 43 50 62 74 83 77 62 53 40 33

Unit Sales 144,908 120,032 103,917 90,866 60,110 36,357 16,002 29,445 63,523 81,847 112,818 130,423

From these data, you have created the following column chart to show the mean daily high temperature by month for this city. Now you want to add the information to this chart to show the number of cups of hot chocolate that were sold each month.

c. You want to add information on the continent of the nation in which headquarters for the top 50 companies in an industry are located to the following column chart that shows the number of these headquarters by nation.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

d. You have been asked by a real estate agent to use the following data to create a chart that provides insight into the nature of the relationship between the sales price and number of days on the market for homes she has recently sold.

Sales Price $247,412 $249,787 $194,955 $173,612 $171,299 $281,197 $264,477 $264,838 $261,819 $293,953 $296,002 $167,136 $334,063 $332,340 $264,066 $255,070 $185,572 $314,198 $256,183 $230,741 $274,552 $262,332 $219,969 $253,708 $245,114 $296,920 $295,866 $270,353 $202,422 $214,206

Days on the Market 58 60 34 55 55 62 25 50 30 42 32 38 33 32 47 55 29 31 42 63 38 45 39 41 55 49 25 59 55 53

Neighborhood East Highland Sebastian Hargrove Hills Hargrove Hills Sebastian Sebastian Hargrove Hills East Highland East Highland East Highland East Highland Hargrove Hills Hargrove Hills Manafort Falls Manafort Falls Manafort Falls East Highland East Highland Manafort Falls Sebastian Manafort Falls Manafort Falls Hargrove Hills East Highland Sebastian Manafort Falls Hargrove Hills Manafort Falls Sebastian East Highland

You have created the following scatter chart. The real estate agent has asked you to add the information on the neighborhood in which each of these homes is located to the scatter chart you have created.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

e. You have been given the following data on monthly change in number of subscribers to several online publications devoted to popular hobbies. You have now been asked to add color to this display to indicate whether the number of subscribers is increasing or decreasing each month.

Jan

Feb

Mar

Apr

May

Jun

Sporting Goods

0.9%

−0.7%

Philatelist Quarterly

0.5%

0.1%

American Spelunker

0.2%

Home Cooks

0.5%

Jul

Aug

−0.1%

0.2%

0.2%

0.5%

−0.3%

1.6%

0.3%

−0.1%

0.5%

0.5%

−0.9%

−0.1%

−1.6%

0.6%

1.6%

−1.4%

0.0%

−0.1%

0.6%

−0.9%

0.2%

1.2%

0.8%

−0.3%

1.2%

0.5%

Sep

Oct

Nov

Dec

1.2%

0.3%

−0.8%

0.9%

0.1%

−0.4%

−1.2%

0.3%

−1.3%

−1.2%

−0.8%

0.4%

0.6%

−1.4%

−0.6%

0.3%

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9

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color Classic Literature Digest Numismatics Magazine Gardening World

0.2%

−0.1%

−0.1%

0.0%

0.7%

−0.5%

Knitting News

1.1%

Online Gamer Popular Photographer

1.1% −0.6%

0.5%

0.4%

0.0%

0.5%

0.4%

0.5%

−1.8%

1.2%

−1.0%

1.2%

0.7%

0.3%

−0.9%

0.0%

−0.7%

−1.4%

−0.1%

0.4%

1.2%

0.0%

1.0%

−0.7%

1.4%

0.1%

1.2%

1.3%

1.4%

1.5%

−0.6%

0.8%

−1.2%

0.9%

1.6%

0.9%

1.0%

−1.2%

−0.3%

1.5%

−0.3%

0.6%

−0.2%

−0.5%

1.2%

1.1%

0.5%

1.8%

1.1%

0.2%

0.1%

0.4%

1.0%

1.4%

2.1%

0.1%

0.8%

1.4%

−0.1%

−1.0%

−0.4%

−0.7%

0.7%

0.8%

Solution: a. Diverging color scheme − This is a quantitative variable for which we are interested in how far values are below zero (losses) or above zero (profits). b. Sequential color scheme − This is a quantitative variable for which we are interested in how far values are above the minimum possible value (zero). c. Categorical color scheme − This is a categorical variable. Its values indicate group or category membership. d. Categorical color scheme − This is a categorical variable. Its values indicate group or category membership. e. Diverging color scheme − This is a quantitative variable for which we are interested in how far values are below zero (decreasing subscribers) or above zero (increasing subscribers).

5. Considering Colorblindness in the Design of a Chart. Four design artists (Frances Bittinger, Dorian Martin, Bill Zander, and Mariana Knoop) of a regional marketing research firm’s graphic arts department have each designed a chart for use in a presentation to a team of Happy Lawn landscaping service executives, two of whom are colorblind. Each has designed a heat map showing the relative percentage change in the number of customers various lawn care services experienced over the past year in several Midwestern states: Illinois (IL), Indiana (IN), Michigan (MI), Minnesota (MN), Ohio (OH), and Wisconsin (WI).

Explain why each of these charts may or may not be difficult for the colorblind members of the team of Happy Lawn landscaping service executives to visually process. LO 6 Percentage Change in Customers (by Frances Bittinger)

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10

1.4%

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Percentage Change in Customers (by Dorian Martin)

Percentage Change in Customers (by Bill Zander)

Percentage Change in Customers (by Mariana Knoop)

Solution: Because Bittinger’s heat map uses shades of red and green with no other indication of the relative changes in number of customers, an audience member who is red-green colorblind may have difficulty visually processing this chart.

Because Martin’s heat map uses shades of yellow and blue with no other indication of the relative changes in number of customers, an audience member who is yellow-blue colorblind may have difficulty visually processing this chart.

Although Zander’s heat map uses shades of red and green, it also includes the percentage change in customers for each cell in the heat map. All audience members, whether they are or are not colorblind, will be able to visually process this chart. However, it would be better to choose colors other than red and green for this divergent color scheme due the prevalence of red-green colorblindness. The inclusion of the actual numbers in the cells of this heat map reinforces which cells represent increased sales and which cells represents decreased sales, but it also increases clutter.

Knoop’s heat map uses shades of orange and blue so all audience members, whether they are or are not colorblind, will be able to visually process this chart.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

6. Identifying Mistakes in the Use of Color in a Column Chart. According to USA Today, the headquarters of over one-third of all Fortune 500 (F500) companies are located in one of six U.S. metropolitan areas: Chicago, Dallas-Ft. Worth, Houston, Minneapolis-St. Paul, New York, and San Francisco. The following chart displays the number of F500 headquarters for each of these metropolitan areas. LO 6

Explain what color is being used to uniquely communicate in this chart, what aspects of the use of color in this chart are ineffective, and how the weakness(es) in the use of color in this chart could be corrected. Also indicate all other revisions you would make to improve this chart.

Solution: Color is used in conjunction with the legend to tell the audience which bar represents each metropolitan area in this chart. This requires the audience to go back and forth between the bars and the legend to make these associations and so creates unnecessary eye travel. Furthermore, metropolitan area has six unique values, but the chart uses only three unique colors; it uses blue for both Chicago and Minneapolis-St. Paul, red for both Dallas and New York, and yellow for both Houston and San Francisco with no identified reason.

We can correct the ineffective use of color in this chart by using a single color for all bars, eliminating the legend, adding a horizontal axis title, and using horizontal axis labels to indicate the metropolitan areas.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

The resulting chart does not confuse the audience with its use of color, is less cluttered, and requires less eye travel, so it is much easier to understand.

7. Identifying Mistakes in the Use of Color in a Bar Chart. The most widely grown lawn turf grasses in the southeastern US are warm-season grasses: bahiagrass, bermudagrass, centipedegrass, St Augustinegrass, and zoysia. Dana Tanner, crew chief with Holiday Grass lawn care service in Birmingham, Alabama, is now planning her resource needs for the upcoming summer. Each of these grasses has different fertilizer and direct sunlight needs, drought and heat tolerance, growth rate, and disease and weed resistance. Therefore, it is important that Ms. Tanner understand the number of lawns of each grass in her district when planning her resource needs for the upcoming summer. To develop a better understanding of the number of lawns of each grass in her district, she observes and records the type of lawn for a random sample of 500 homes in her district, and she summarizes her results in the following chart. LO 6

Explain what information color is being used to uniquely communicate in this chart, what aspects of the use of color in this chart are ineffective, and how could the weakness(es) in the use of color in this chart be corrected.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Solution: Ms. Tanner’s use of a single hue is appropriate, and her selection of green takes advantage of color symbolism for grass/nature. However, the different levels of luminance she uses create a gradient that has no apparent meaning. If luminance is used to convey some other characteristic about these types of grasses such as fertilizer needs, direct sunlight needs, drought tolerance, heat tolerance, growth rate, disease resistance, or weed resistance, the chart should be labeled so the audience will understand how to interpret different levels of luminance. If luminance is not being used to convey some other characteristic about these types of grasses, the chart should be revised so the color is the same for all bars. An example is shown in the following chart.

APPLICATIONS 8. Comparing the Number of Fortune 500 Headquarters in Six US Metropolitan Areas.

Consider the number of Fortune 500 (F500) headquarters in the six U.S. metropolitan areas (Chicago, Dallas-Ft. Worth, Houston, Minneapolis-St. Paul, New York, and San Francisco) that are home to the greatest numbers of F500 headquarters. Modify the following column chart (from Problem 6) displaying these data, which is provided in the file f500metros_chart, so that it uses color more effectively. Also make all other necessary revisions to improve this chart. Explain why the changes you have made produce a chart that is superior to the original bar chart from Problem 6. LO 5

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Solution: We can correct the ineffective use of color in the chart in Problem 6 by using the same color for all bars. In the following chart, we make all the bars blue, eliminate the legend, add a horizontal axis title, and use horizontal axis labels to indicate the metropolitan areas.

By eliminating the ambiguity introduced through differences in color and using horizontalaxis labels to identify the metropolitan areas, we reduce the audience’s cognitive load without sacrificing any information on the chart. This also allows us to eliminate the legend, further reducing the unnecessary use of ink. The resulting chart communicates more effectively than the original chart from Conceptual Problem 6.

9. Frequency of Types of Grass. Consider the number of lawns from a sample of 500 Birmingham, Alabama, homes that have various types of warm-season grasses (bahiagrass, bermudagrass, centipedegrass, St Augustinegrass, and zoysia) in their lawns. The following bar chart of these data (from Problem 7) is provided in the file holidaygrass_chart. LO 5

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

a. Modify this bar chart, which is provided in the file holidaygrass_chart, so that it uses color more effectively. Also declutter the chart where possible. Explain why the changes you made produce a chart that is superior to the original bar chart in the file holidaygrass_chart. b. Modify bar chart in part a to highlight Bermudagrass.

Solution: a. We retain the single green hue on all of the bars. Since differences in luminance are not communicating anything about the data, we revise the chart so the level of luminance is equal for all bars. The color of these bars is generated by Hue = 104, Sat = 255, and Lum = 110.

By eliminating the ambiguity introduced through differences in luminance, we reduce the audience’s cognitive load without sacrificing any information on the chart.

By removing the horizontal- and vertical-axis titles, we decrease the ink-data ratio and declutter the chart.

The resulting chart uses color more effectively and communicates more effectively than the original chart. b. We can differentiate Bermudagrass by decreasing its luminance to make it darker than the other bars, or by increasing its luminance to make it lighter than the other bars.

Because the bars in the chart in part a have a moderate luminance (Lum = 110), we elect to differentiate Bermudagrass by decreasing its luminance to Lum = 60 to make it darker than the other bars and create a stark contrast.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

The difference in luminance clearly distinguishes Bermudagrass from the other grasses in this bar chart.

10. T-Shirt Sales over Time. You have been asked to prepare a line chart that shows monthly sales for the past year for the four colors of slub cotton t-shirts that are manufactured and marketed by the Great Plains Garment Company (GPGC). GPGC sells all of its products online. You obtain the data from GPGC’s sales department and produce the following chart in Excel.

Upon reviewing your chart, you realize that you could make it more effective through appropriate use of color symbolism. After deciding to use the color of each t-shirt for its line on the chart, you obtain the following image showing the four colors of GPGC’s slub tshirts from its website collection. The data, the original chart, and the following image (which can be cut out of the Excel spreadsheet and pasted into PowerPoint) are included in the file gpgc_chart. LO 2

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

a. Use PowerPoint and the Eyedropper tool to determine the hue, saturation, and luminance of the predominant color of each t-shirt. List the values of the hue, saturation, and luminance of each color. b. Revise the line chart in the file gpgc_chart so the color of each line corresponds to the color of the associated slub t-shirt from part a. Also change the color of the text in the label at the end of each line to match the color of the corresponding slub t-shirt.

Solution:

a.

Hue

Saturation

Luminance

Sea Foam

92

200

176

Fuchsia

0

255

185

Plum

201

119

195

Azure

149

255

128

b.

The use of symbolic color on this chart makes it much easier for the audience to understand. You could also consider removing the labels at the ends of the four lines since the colors of the lines serve as indicators of the slub t-shirt colors they represent.

11. The Relationship between Wins and Attendance in Baseball. In doing an analysis of the economics of baseball in your state, you collect data on annual home game attendance and number of wins from 2000 to 2019 for the state’s two baseball teams, the Komodos and the Condors. In order to communicate the nature of the relationship between annual home game attendance and number of wins for the two teams over that period, you produce the following scatter chart in Excel.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

The chart shows a mildly positive relationship between annual home game attendance and number of wins for each team. The chart also shows the Condors have routinely won more games than the Komodos but have generally had lower attendance. However, you see a way to improve this chart by using the predominant color of each team’s uniform instead of the Excel default colors for the points that represent the two teams.

You obtain the following images of the two team’s home jerseys from their respective websites and paste them into the file attendwins_chart that also contains the data and your original chart. LO 4

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

a. Use PowerPoint and the Eyedropper tool to determine the hue, saturation, and luminance of the predominant color of each jersey. List the values of the hue, saturation, and luminance of each color. Images of the two jerseys are included in the file attendwins_chart and can be cut and pasted into PowerPoint. b. Revise the scatter chart in the file attendwins_chart so the color of each series corresponds to the color of the corresponding team’s jersey from part a.

Solution: a. Use PowerPoint and the Eyedropper tool to determine the hue, saturation, and luminance of the predominant color of each jersey. List the values of the hue, saturation, and luminance of each color.

Hue

Saturation

Luminance

Komodos

247

224

99

Condors

156

101

47

b. Revise the scatter chart in the file attendwins_chart so the color of each series corresponds to the color of the corresponding team’s jersey from part a.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

The use of symbolic colors on this chart will make it much easier for the audience to understand if the audience members know the team colors of the Komodos and the Condors.

12. Composition of Boise Regional Medical Center Nursing Staff. Boise Regional Medical Center (BRMC) is completing its annual report for the Idaho Board of Trustees. One section of this report is devoted to an analysis of the composition of the BRMC nursing staff. The current draft of this report includes the following bar chart that shows the percentage of the nursing staff by classification. This chart is included in the file brmc_chart.

In its review of the draft report, management has noted that some audience members may consider the color of the bars in this chart to be inappropriate for BRMC because red is often associated with anxiety. Management has requested that the chart be revised using a color that is more calming. Revise this chart using a color for the bars that is generally considered to be comforting and calming. Refer to Figure 4.13 to identify the hue you will use. LO 2 Solution: Figure 4.5 identifies green and blue as colors generally associated with the traits comforting and calming. We can also create a less harsh feel by using a relatively high value of luminance to lighten the color we choose.

The bar chart that follows uses a light shade of green (Hue = 100, Sat = 255, Lum = 200) for the bars.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Alternatively, the bar chart that follows uses a light shade of blue (Hue = 156, Sat = 255, Lum = 200) for the bars.

Either of these options would be considered by most audience members to be less harsh and more soothing than the original bar chart.

13. Relationship between University Enrollment and Changes in Mean Faculty Salary. The Ohio Board of Regents (OBR) is preparing its five-year report on the state of higher education in Ohio. The current draft of the report includes a scatter chart of enrollment and the percentage five-year change in average faculty salary for the 16 largest four-year institutions in the state. The scatter chart that is included in the current draft of the report follows and is provided in the file ohhighered_chart.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

On reviewing the current draft, one of the members of the OBR has asked that you add an indication of which of these universities is private to this scatter chart. Use color to distinguish the private universities (Case Western Reserve University, University of Dayton, Xavier University, Franklin University, University of Findlay) on the scatter chart from the public universities. What does this additional information tell you? LO 3 Solution: The markers corresponding to the five private universities in the following scatter chart are orange (Hue = 17, Sat = 214, Lum = 143), and the markers associated with the public universities remain blue (Hue = 148, Sat = 151, Lum = 152).

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

The contrast between orange and blue makes it easy to find the private universities.

We can now see that the public universities tend to have higher enrollments than the private universities, and they tend to have slightly larger five-year changes in mean faculty salary. Case Western Reserve University has a very different profile from the other four private universities on the chart. Its enrollment is similar to the other private universities, but its five-year change in mean faculty salary is much larger.

14. Viewership of Top Rated Scripted Television Shows. The 18−49 age group is an extremely lucrative demographic for television networks. Advertisers pay a premium to reach consumers in this age group with their advertising. The following column chart shows the number of viewers in millions that the top ten scripted series averaged during the 2019−2020 television season.

It is also important for this chart to show which television network (ABC, CBS, FOX, NBC) broadcasts each show. The networks that broadcast these shows are: ABC: CBS: NBC:

The Good Doctor, Modern Family, Grey’s Anatomy Young Sheldon, NCIS New Amsterdam, Chicago Med, Chicago Fire, Chicago PD, This Is Us

Use color to add this information to the original bar chart, which is provided in the file top10tv2020_chart. Will your chart be difficult for colorblind audience members to visually process? Explain. LO 3 Solution: The following bar chart uses red (Hue = 0, Sat = 255, Lum = 100) for ABC shows, green (Hue = 104, Sat = 255, Lum = 180) for CBS shows, and blue (Hue = 148, Sat = 255, Lum = 152) for NBC shows.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

We can now see easily distinguish between the networks on this chart. In addition to differentiating between the networks by hue, we use different levels of luminance for the three networks to create a chart that colorblind audience members should also be able to visually process.

15. Relationship between Estimated and Actual Time to Complete a Housepainting Job. Charlene & Daughters (C&D) employees 20 crews of interior house painters that work throughout the northwest United States. The leader of each crew is responsible for visiting potential job sites and developing an estimate of the number of hours it will take to complete a job based on a C&D formula that considers the square footage of the surfaces to be painted, the amount and type of trim, and whether ceilings are to be painted. The crew leader also has the latitude to make subjective adjustments based on other factors that are not considered by the formula.

C&D is now assessing the accuracy of its estimates of the time it will take to complete jobs. It has collected the estimated and actual times to complete each of the ten most recent jobs for each crew, and it has entered these data into the file cd_chart. A portion of the data, which includes the name of the crew leader, the estimated time to complete the job, and the actual time to complete the job, follows.

Repair Person Briggs Briggs Briggs Briggs Briggs Briggs Briggs Briggs Briggs Briggs Cobb Cobb ⁞

Estimated Hours 25.8 62.5 75.6 75.7 61.9 6.1 38.2 52.2 63.1 66.9 37.1 45.0 ⁞

Actual Hours 29.4 66.3 50.9 77.0 74.8 5.8 36.3 55.3 69.3 77.5 32.6 46.6 ⁞

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Taubee Taubee Vincent Vincent Vincent Vincent Vincent Vincent Vincent Vincent Vincent Vincent

6.8 54.1 25.7 80.9 20.8 24.8 74.4 18.3 74.6 58.7 37.5 68.7

6.0 62.5 20.3 93.6 20.6 25.7 84.7 18.3 81.2 52.9 41.1 56.0

C&D has also used these data to produce a scatter chart, and it has used color to differentiate between the crews on this chart. The chart, which follows, is also included in the file cd_chart. Note that the legend identifies each crew by the name of its crew leader.

LO 3

a. C&D would like to describe the accuracy of its estimates using a chart. If C&D’s estimated hours matched the actual hours perfectly, then all points in this scatter chart would lie on a diagonal line that is 45° from the origin. Draw a diagonal line at 45° from the origin through the chart to help you assess the accuracy of C&D’s © 2025 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

estimates. To draw this 45° line, draw a line that passes through the points (0, 0); (40, 40); (80, 80); and (120, 120) on the chart. Would you advise that C&D incorporate this line into its scatter chart? Why or why not? b. Revise the chart so all of the points are blue (Hue = 148, Sat = 151, Lum = 152). Is the use of color in this chart more effective than the use of color in the chart in part a?

Why or why not? c. C&D has indicated some concern over recent estimates of the crew headed by Cobb.

Use color on the scatter chart to draw attention to the jobs completed by the crew headed by Cobb and interpret the results.

Solution: a. The scatter chart with a line at 45o from the origin through the chart follows.

This chart shows that C&D underestimates the number of hours it will take to complete a job more often than it overestimates the number of hours it will take to complete a job. It also shows that this happens more often for jobs that take the longest times to complete, and that the differences between the estimated number of hours it will take to complete a job and the actual number of hours it will take to complete the job increase as the number of hours to complete the job increases.

The line drawn at 45o from the origin through the chart should be incorporated. It makes it much easier for C&D to see how often it underestimates and overestimated the time it takes to complete its jobs because: • The vertical distance of any point from the line shows the relative error in the estimated number of hours it will take to complete the corresponding job • Points below the line are instances in which C&D has overestimated the number of hours it will take to complete the job

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

• •

Points above the line are instances in which C&D has underestimated the number of hours it will take to complete the job Points on the line are instances in which C&D has perfectly estimated the number of hours it will take to complete the job

b. Assigning a unique color to each crew on the scatter chart and providing a legend will result in the use of 20 colors, and this is difficult for the audience to process. It also requires a great deal of eye travel. If C&D is only concerned with the accuracy of its estimates across the company and not with the accuracy of estimates for any individual crew, the chart should use the same color for all points. Such a chart that uses blue (Hue = 148, Sat = 151, Lum = 152) for all points follows.

Using a single color for all points and eliminating the legend makes this chart much less cluttered and much easier to understand.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

c. The following scatter chart uses orange (Hue = 17, Sat = 214, Lum = 143) for the points associated with the Cobb crew.

Using orange for the Cobb crew and blue for all other crews makes it easy to find the jobs done by the Cobb crew in this scatter chart. Cobb has tended to underestimate the number of hours it will take to complete jobs (eight out of 10 points associated with the Cobb Crew lie above the line, and several are relatively far above the line).

16. Production of Laptop Computer Screens. CrystalClear, Inc. manufactures low-resolution 15-inch screens for inexpensive laptop computers at plants in five states (California, Nebraska, North Carolina, North Dakota, and Texas). The number of units produced by each plant is provided in the following table and is provided in the file crystalclear.

Plant Location Texas North Dakota California Nebraska North Carolina

Units Produced 54,210 61,002 75,143 79,210 82,157

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

CrystalClear, Inc. management suspects that its larger plants are producing the greatest number of units. The square footage for each plant follows and is also provided in the file crystalclear.

Plant Location Texas North Dakota California Nebraska North Carolina

Sq Ft 47,000 53,000 65,000 63,000 70,000

Provide a scatter chart that of the plant data to provide insight into the nature of the relationship between units produced and size of the plant for the five plants and highlight the Nebraska plant. LO 4 Solution: We use a scatter chart to emphasize the nature of the relationship between units produced and size of the plant for the five plants. We also change the color of the point and data label associated with the Nebraska plant to orange (Hue = 17, Sat = 214, Lum = 143).

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Through its use of the preattentive attribute of spatial position, this scatter chart effectively communicates the nature of the relationship between units produced and square footage for the five plants. As expected, the number of units produced and size of plant are positively related; larger values of one of these variables is associated with larger values of the other variable.

The preattentive attribute of color is used to highlight the Nebraska plant. By using orange for Nebraska’s point and its label, we make it easy for the audience to compare this plant to the other four plants.

17. Pet Food Sales by State. Pet Fare, Inc. produces high-end refrigerated pet food and ships it anywhere in the United States. Total Pet Fare sales of cat food and dog food by state for the previous year are given in separate worksheets in the file catsanddogs. LO 5 a. Create a geographic information system (GIS) map that uses a sequential color scheme to represent total Pet Fare cat food sales by state. Use orange for the color for this choropleth map. What information does this chart convey to the audience? b. Create a geographic information system (GIS) map that uses a sequential color scheme to represent total Pet Fare dog food sales by state. Use blue for the color for this choropleth map. What information does this chart convey to the audience? c. Create a scatter chart that enables the audience to better understand the relationship between total cat food sales and total dog food sales for the states. What does this chart tell you about the relationship between total cat food sales and total dog food sales? d. Use color to highlight Wyoming in the scatter chart from part c. What does this chart tell you about total cat food sales and total dog food sales in Wyoming relative to the other states? e. What inherent weaknesses do you see in the analysis performed in parts a−c? How would you address these issues? (Hint: Consider the disparities in the sizes of the statewide markets.)

Solution: a.

Pet Fare’s cat food sales are highest in California, Florida, and New Jersey, and lowest in Wyoming. There does not appear to be any geographical pattern in Pet Fare’s cat food sales.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

b.

Pet Fare’s dog food sales are highest in California, Florida, Georgia, and Texas, and lowest in Wyoming. There does not appear to be any geographical pattern in Pet Fare’s dog food sales. c. The following scatter chart provides insight into the relationship between total cat food sales and total dog food sales by state.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

The relationship between total cat food sales and total dog food sales is positive; higher sales in one category generally coincide with higher sales in the other category. d. In the following scatter chart, we use dark orange (Hue = 17, Sat = 255, Lum = 100) to indicate which point corresponds to Wyoming and light blue (Hue = 148, Sat = 151, Lum = 200) for the points corresponding to all other states.

Wyoming is near the bottom of states in both cat food sales and dog food sales.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

e. Both cat food sales and dog food sales are generally highest in densely populated states, which likely have the largest cat and dog populations, and lowest in sparsely populated states, which likely have the smallest cat and dog populations.

• A gradient could be applied to the color of the points to show relative populations of the corresponding states (i.e., lower luminance/darker colors could be associated with states with larger populations).

• A bubble chart could be created with the same axis as the charts in parts a−c, and the size of the bubbles could be used to show relative populations of the corresponding states (i.e., larger bubbles could be associated with states with larger populations).

• Data on the cat and dog populations of each state could be used to calculate dollars per capita for the cat and dog populations for each state.

Any of these analyses would allow Pet Fare to better understand their sales at the state level relative to the sizes of the statewide markets.

18. Alabama Unemployment Rate by County. The Labor Market Information Division of the Alabama Department of Labor is preparing its monthly report on unemployment, and it would like to include a choropleth map that shows unemployment rate by county. Use the unemployment rate for each of Alabama’s 77 counties provided in the file alabamaunemployment to create this choropleth map. What does this map tell you about where the highest rates of unemployment are in Alabama? LO 5 Solution: The GIS map of unemployment rates in Alabama by county follows.

The highest rates of unemployment are in counties that run roughly east to west across the southern portion of the center of Alabama.

19. Life Expectancy of LED Bulbs. Capital Electrics (CE) advertises that the life expectancy of the LED bulbs it produces is 28,000 hours. The electrical engineering team at CE has designed a test to assess the impact of ambient temperature on the LED light bulbs CE manufactures.

Using strict temperature controls, the engineers set up rooms starting at 0o Fahrenheit in 10-degree increments to 160o Fahrenheit. They then put a bulb at each wattage from 7 watts to 25 watts in a light fixture in each room, turn on the fixtures, and record the number of hours until each bulb fails. The data they have collected are provided in the file ledbulbs.

Use these data to create a heat map of the life of the LED bulbs by their wattage and the ambient temperature of the room in which they are placed. In the New Formatting Rule dialog box of Conditional Formatting, enter 3-Color Scale for Format Style, enter

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Number in the Type: box of the Midpoint column, enter 28000 in the Value: box of the Midpoint column, and in the Color: row, use orange (Hue = 17, Sat = 255, Lum = 115) for values below 28,000, white for the Midpoint, and blue (Hue = 156, Sat = 255, Lum = 48) for values above 28,000. Mask the cell values and create a legend that tells the audience that orange corresponds to low bulb lives less than 28,000 hours, blue corresponds to bulb lives greater than 28,000 hours, and the color grows darker as the deviation of the bulb life from 28,000 increases in either direction. LO 5 Solution: The resulting heat map follows.

The predominance of orange in the right side of the heat map shows that the life of CE’s LED bulbs is shorter at higher ambient temperatures. Furthermore, the orange is darker in the lower right corner of the heat map, indicating that at higher ambient temperatures the life of the bulb declines faster as the wattage of the bulb increases.

20. Comparing Regional Market Shares. Bay Side Manufacturing produces small leather goods such as wallets, travel organizers, toiletry kits, briefcases, and folios. The company has a 16% share in the U.S. travel organizers market, but management is concerned that its market share in the southeastern United States lags behind its national share. Bay Side’s monthly share of the travel organizers market for the past year in 15 major cities in the southeastern United States is provided in the file bayside. A portion of the data is shown in the following table.

Atlanta Baltimore Baton Rouge Birmingham Charlotte Jacksonville Louisville Memphis

Jan 0.142 0.172 0.133 0.087 0.088 0.188 0.217 0.107

Feb 0.145 0.199 0.084 0.105 0.112 0.188 0.214 0.115

Market Share Mar Apr …

0.137 0.152 …

0.177 0.189 …

0.137 0.123 …

0.105 0.096 …

0.094 0.100 …

0.190 0.173 …

0.164 0.190 …

0.132 0.111

Nov 0.132 0.181 0.144 0.118 0.069 0.197 0.189 0.125

Dec 0.152 0.185 0.097 0.121 0.077 0.185 0.192 0.115

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 4: Purposeful Use of Color

Miami Nashville New Orleans Raleigh Richmond Tampa Virginia Beach Washington

0.162 0.053 0.129 0.156 0.178 0.119 0.172 0.232

0.158 0.054 0.161 0.188 0.156 0.115 0.174 0.241

0.158 0.074 0.159 0.162 0.183 0.108 0.129 0.204

0.157 0.081 0.189 0.150 0.157 0.145 0.166 0.191

… … … … … … … …

0.180 0.083 0.194 0.190 0.158 0.144 0.164 0.207

0.169 0.099 0.155 0.191 0.145 0.110 0.191 0.243

Use these data to create a heat map of Bay Side’s monthly share of the travel organizers market for these 15 southeastern U.S. cities. In the New Formatting Rule dialog box of Conditional Formatting, enter 3-Color Scale for Format Style, enter Number in the Type: box of the Midpoint column, enter 0.16 in the Value: box of the Midpoint column, and in the Color: row, use orange (Hue = 17, Sat = 214, Lum = 143) for values below 0.16 and blue (Hue = 156, Sat = 255, Lum = 48) for values above 0.16. Mask the cell values and create a legend that tells the audience that orange corresponds to market shares less than 14%, blue corresponds to market shares greater than 14%, and the color grows darker as the deviation of the market share from 14% increases in either direction.

What message will this map communicate to an audience? Will this chart be difficult for colorblind audience members to visually process? Explain. LO 5 Solution: A heat map that uses intensity of orange to indicate the amount below the national 16% market share and intensity of blue to indicate the amount above the national 16% market share follows.

There are a few cities in the southeastern U.S. in which Bay Side’s share of the travel organizers market is consistently at or above its national market share, but market share is generally below the national 16% level throughout the southeast. There also does not appear to be a seasonal pattern to these market shares.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 5: VISUALIZING VARIABILITY

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1 CONCEPTUAL ............................................................................................................................. 1 APPLICATIONS.......................................................................................................................... 13

END OF SECTION PROBLEM SOLUTIONS CONCEPTUAL 1.

Histogram Bin Widths for Boating Customers. Based on a survey of 1046 individuals who recently took the boat cruise on Lake Havasu, Rochambeau Boating is analyzing the percent frequency distribution of its customers’ ages. An analyst has created four histograms by varying the bin size. Rochambeau seeks a visualization of the customer age distribution that captures general trends in the data, but does not blur patterns by grouping customers with disparate ages (and therefore behaviors) into the same bins.

Which histogram would you recommend that the analyst use to describe the customer age distribution? LO 2 i.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

ii.

iii.

iv.

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2

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

Solution: Histogram (ii) is the best choice as it smooths out trends in the data without overgeneralizing the characteristics. The bin size in histogram (i) appears to be too small and the resulting visualization is noisy and jagged. The bin size in histogram (iii) appears to be too big as it blurs the small peak of extremely young customers. The level of aggregating in histogram (iv) is too large and groups customers from too wide of an age range (15 years).

2. Stacked Column Chart for Boating Customers. Based on a survey of 1046 individuals who recently took the boat cruise on Lake Havasu, Rochambeau Boating is analyzing the demographics of its customers. It is believed that the sample (388 females and 658 males) is representative of Rochambeau’s overall customer population. An analyst has created the following chart depicting the age and sex distribution of the survey respondents. LO 3

Which of the following statements accurately assess this stacked column chart? (Select all that apply.) i. The use of color is unnecessary and distracting. ii. The stacked orientation makes it difficult to compare the shape of the age distributions of male and female customers. iii. A strength of this chart is how the stacked orientation visualizes the overall age distribution and how the number of customers in each age bin are split into male and female categories. iv. It would be better to orient this chart vertically as a stacked bar chart.

Solution: ii and iii 3. Clustered Column Chart for Boating Customers. Based on a survey of 1046 individuals who recently took the boat cruise on Lake Havasu, Rochambeau Boating is analyzing the demographics of its customers. It is believed that the sample (388 females and 658 males) is representative of Rochambeau’s overall customer population. An analyst has created the following chart depicting the age and sex distribution of the survey respondents. LO 2, 3

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3

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

a. Which of the following statements accurately criticizes this clustered column chart? i. There are too few bins. ii. The alternating male and female frequency columns cast a disrupted visualization of the distributions. iii. The use of color is unnecessary and distracting. iv. A stacked column chart would compare females and males better. b. Which of the following is a better way to visualize these data to facilitate the comparison of the age distributions of female and male customers? i. Stacked column chart ii. Strip chart iii. Frequency polygon iv. Stem and leaf chart Solution: a. ii b. iii 4. Age Pyramid for Boating Customers. Based on a survey of 1046 individuals who recently took the boat cruise on Lake Havasu, Rochambeau Boating is analyzing the demographics of its customers. Treating the sample of 388 females and 658 males separately, an analyst is interesting in comparing how the ages of the female customers are distributed as a percentage of the 388 females surveyed, and how the ages of the 658 male customers are distributed as a percentage of the 658 males surveyed. An analyst has created the following chart depicting the age and sex distribution of the survey respondents. LO 3

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4

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

a. Which of the following statements accurately criticizes this chart? i. Orienting the frequency bars for females and males end-to-end makes it harder to visually compare their magnitudes. ii. There are too many bins. iii. The use of color is unnecessary and distracting. iv. Rotating the chart by 90 degrees would allow for better binwise comparison of females and males. b. Which of the following is a better way to visualize these data to facilitate the comparison of the age distributions of female and male customers? i. Clustered column chart ii. Strip chart iii. Violin chart iv. Frequency polygon Solution: a. i b. iv 5. Distribution Deviation Chart for Boating Customers. Based on a survey of 1046 individuals who recently took the boat cruise on Lake Havasu, Rochambeau Boating is analyzing the demographics of its customers. Treating the sample of 388 females and 658 males separately, an analyst is interested in comparing how the ages of the female customers are distributed as a percentage of the 388 females surveyed, and how the ages of the male customers are distributed as a percentage of the 658 males surveyed. An analyst has created the following chart computing the difference in these percentages for each age bin. LO 3

a. Which of the following statements accurately criticizes this chart? i. There are too few bins. ii. There are too many bins. iii. The chart needs to use color differentiation. iv. This chart provides no insight on the shape of the age distributions for female and male customers and the differences computed are highly dependent on the bins used.

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5

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

b. Which of the following is a better way to visualize these data to facilitate the comparison of the age distributions of female and male customers? i. Kernel density chart ii. Clustered column chart iii. Frequency polygon iv. Strip chart Solution: a. iv b. iii 6. Daily Temperature Strip Charts. Aspiring meteorologist Jesse Kosch has collected data on the daily high temperature in Valentine, Nebraska, over an entire year. Jesse then used a strip chart to display each day’s high temperature by month. LO 4

a. Which of the following statements accurately criticizes this chart? i. It is not clear what each data point represents. ii. The chart suffers from occlusion as there is not a distinct data point for each day in each month. iii. A line chart would better display this data. iv. The chart needs to use color differentiation. b. How could Jesse best improve this visualization? i. Differentiate each month with a different color ii. Jitter each data point vertically iii. Change horizontal axis to day of year and plot as time series chart iv. Use hollow dots instead of solid dots and horizontally jitter each data point Solution: a. ii b. iv

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

7. Histogram for Assessed Home Values. Chris Fultz, a realtor at Betelgeuse Realty, is conducting research on assessed home values in a local suburb. Chris has constructed the following histogram. LO 2, 5, 6

Which box and whisker chart corresponds to the histogram? i.

ii.

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7

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

iii.

iv.

Solution: Box and whisker chart (iv) corresponds to the histogram. The histogram is skewed to the right by some extremely large home values, which are depicted as outliers in (iv).

8. Frequency Polygon for Assessed Home Values. Abbie Aburizek, a realtor at Alamo Acres, is conducting research on assessed home values in a local suburb. Abbie has constructed the following frequency polygon. LO 2, 5, 6

Which box and whisker chart corresponds to the frequency polygon? © 2025 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

8

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

i.

ii.

iii.

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9

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

iv.

Solution: Box and whisker chart (ii) corresponds to the histogram. The histogram is skewed to the left by a few extremely small home values, which are depicted as outliers in (ii).

9. Life Insurance Analysis. Josh Bell, an actuarial scientist for Yolo Life Insurance, has created the following box and whisker charts of the age at death for a randomly drawn sample representative of potential clients. LO 6

Which of the following assessments are true? i. The distributions are positively skewed; females live longer on average. ii. The distributions are negatively skewed with several outliers of extremely small values; females live longer on average. iii. The distributions are symmetric; the mean and median values are the same. iv. There are no outliers in either sample; both the female and male distributions have the same shape Solution: Assessment (ii) is true.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

10. Restaurant Delivery Times. A foodie blog has gathered data on the delivery times for four various restaurant delivery services (CHOMP, Uber Eats, DoorDash, Grubhub). Blog editor Auguste Gusteau has been analyzing the distribution of delivery times for each of these delivery companies and is contemplating how to visually compare the four delivery time distributions. Which of the following would you recommend? LO 3 i. Plotting all four delivery time distributions on a clustered column chart. ii. Using a trellis display arranging the four frequency polygons vertically. iii. Using a collection of six charts each displaying a different pair of delivery time distributions with frequency polygons. iv. Plotting all four delivery time distributions with frequency polygons.

Solution: ii 11. Call Center Response Times. Skylar Diggins is reviewing the performance of four call centers under her management. Twelve observations of the amount of time it took to process refund requests have been collected from each of the four call centers. Based on these observations, the following column chart displays the average service time of each call center. LO 7

a. Why may the interpretation of the average service time from this column chart be misleading? b. How can this chart be improved to provide a more accurate comparison of the average service times at the call centers?

Solution: a. The display of these sample means does not show the uncertainty in these estimates. b. The display of a confidence interval for each mean using error bars would convey the uncertainty in the sample means.

12. Vision Insurance. Before including vision insurance in the benefits package for its 10,000 employees, Valmont Industries wants to confirm that it is desired by a majority of employees. Valmont has taken an employee survey and out of the 100 survey respondents, 55 employees said they would opt into the coverage. An analyst has displayed the results in the following column chart. LO 7

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11

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

a. Why may the results of the sample proportion in this chart be misleading in terms of interpreting the proportion of all 10,000 employees who want vision insurance? b. How can this chart be changed to convey the survey results more accurately?

Solution: a. The display of this sample proportion does not show the uncertainty in this estimate. b. The display of a confidence interval on the proportion using an error bar would convey the uncertainty in the sample proportion. Also, plotting a horizontal line at 0.50 would visually facilitate the comparison to this threshold for majority support.

13. Restaurant Franchising. A restaurant chain particularly popular with college students has collected data on the relationship between quarterly sales of existing restaurants and the size of the college student population in the respective restaurant’s immediate region.

Janice Moore, director of franchising, has constructed a simple linear regression model using quarterly sales as the dependent variable (y) and college student population as the independent variable (x). The data and simple linear regression model are displayed in the chart below. LO 8

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12

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

The development team has identified a promising location for a new franchise that has 10,000 college students living nearby. Based on her simple regression model, Janice predicts that this new franchise would experience quarterly sales of y = 5x + 60 = (5 × 10) + 60 = 110, or $110,000. Janice has highlighted this prediction on her chart. LO 8 a. Why may the results of this chart be misleading? b. How can this chart be changed to convey the survey results more accurately?

Solution: a. The chart does not communicate the uncertainty in the prediction. b. The display of prediction intervals bracketing the simple regression line would convey the uncertainty in the predictions for varying student population sizes.

14. Forecasting Stock Price. To inform his day trading, Jorge Belfort has gathered historical stock price data on Nile Inc., a green energy company he has been researching. Jorge has constructed the following time series chart to display the stock prices as well as his forecasts of the stock price over the next few days.

How can Jorge modify this chart to further communicate any uncertainty associated with his forecast for this stock? LO 8 Solution: The display of prediction intervals bracketing the forecast for future days would convey the uncertainty in the predictions.

APPLICATIONS 15. Most Visited Webs Sites. In a recent report, the top five most-visited English-language websites were google.com (GOOG), facebook.com (FB), youtube.com (YT), yahoo.com (YAH), and wikipedia.com (WIKI). The file websites contains a sample of the favorite website for 50 Internet users. LO 1 a. Using a column chart, visualize the frequency distribution for these data. b. On the basis of the sample, which website is listed most frequently as the favorite website for Internet users? Which is second?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

Solution: a.

b. The most frequent favorite website is google.com (GOOG); second is yahoo.com (YAH).

16. Auditing Travel Expense Reports. Courtney Boyce is currently auditing a sample of the travel expense reports submitted by company employees over the past year. LO 1 a. Using the data in the file travelexpenses, create a percent frequency distribution of the first digit of the expense reported in each report. b. Assessing this distribution with Benford’s Law, does Courtney have any reason to suspect reporting error or fraud? Hint: Treat the first digit of expense amount as a categorical variable (text) rather than as a numerical value.

Solution: a.

b. Comparing this to the relative frequency distribution one would expect from Benford’s Law, we observe that there is a reason to suspect something is amiss with the reports and further analysis should be conducted.

17. University Endowments. University endowments are financial assets that are donated by supporters to be used to provide income to universities. There is a large discrepancy in the size of university endowments. The file endowments provides a listing of many of the universities that have the largest endowments as reported by the National Association of College and University Business Officers. LO 2, 5 © 2025 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

a. Construct a histogram of the frequency counts. b. Comment on the shape of the distribution displayed by the histogram.

Solution:

a.

b. Most of the endowment values are very small, but the distribution is skewed to the right by a few extremely large endowments.

18. Busiest North American Airports. Based on the total passenger traffic, the airports in the file airports are among the busiest in North America. LO 2, 5 a. Construct a histogram of the frequency counts using a bin width of 10 with the first bin starting at a value of 30 million. b. What is the most common passenger traffic range based on this histogram? c. Describe the shape of the histogram.

Solution: a.

b. The most common range of passenger traffic is 40 million to 50 million. c. The passenger traffic distribution is skewed to the right by a few extremely busy airports.

19. Television Viewership of Football Games. Companies considering purchasing ads during televised XFL football games are interested in the viewership of games as a way of estimating the exposure their ads get. The file xfl contains a sample of viewership numbers for XFL games televised on Friday and Saturday nights, respectively. LO 6 a. Construct box and whisker charts on the same chart that compare the viewership distribution of Friday night XFL games to the viewership distribution of Saturday night XFL games. b. Use the box and whisker charts to compare the two distributions.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

c. Use the box and whisker chart of the Friday night XFL games to describe this distribution. d. Use the box and whisker chart of the Saturday night XFL games to describe this distribution.

Solution: a.

b. Generally speaking, Friday night XFL games have a larger viewership than Saturday night XFL games. The 25th percentile of Friday night viewership is larger than the 75th percentile of Saturday night viewership. Both the mean and median of Friday night viewership is much larger than the respective measures for Saturday night viewership. c. The mean and median of the Friday night XFL viewership are approximately the same.

The 25th and 75th percentiles are nearly the same distribution from the median (50th percentile). The whiskers extending from both the 25th and 75th percentiles are roughly the same length. All of these indicate that the distribution of the Friday night XFL viewership is fairly symmetric around a single mode. There a few outliners in Friday night XFL games: a couple games have extremely large viewerships and one game has extremely low viewership. d. The mean is larger than the median of the Saturday night XFL viewership. The median (50th percentile) is closer to the 25th percentile than the 75th percentile. The whiskers extending from the 75th percentile are much longer than the whiskers extending from the 25th percentile. All of these indicate that the distribution of the Saturday night XFL viewership is positively skewed. Many viewership values are relatively small, but there is a tail of infrequent large values. There are two games with extremely large viewerships that are outliers in this distribution.

20. CEO Time in Meetings. A study was conducted to examine how chief executive officers (CEOs) spend their work days. The file ceotime contains a sample of data from this study, which tracked the minutes per day various CEOs spent in meetings. LO 4, 5 a. Construct a strip chart displaying the data making sure to employ techniques to avoid occlusion. b. What is the median amount of time a CEO spends in meetings per day? c. What is the mean amount of time a CEO spends in meetings per day? d. What is the most common amount of time a CEO spends in meetings per day?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

Solution: a. An example of a strip chart with hollow dots and jittering follows.

b. The median is 19 minutes. c. The mean is 18.32 minutes. d. The mode is 15 minutes.

21. Number of Hours Worked per Week by Teachers. According to the National Education Association (NEA), teachers generally spend more than 40 hours each week working on instructional duties. The file teachers contains data on the number of hours worked per week for a sample of high school science teachers and English teachers. LO 4, 5 a. Construct a strip chart comparing the number of hours worked per week for high school science teachers to the number of hours worked per week for English teachers.

Be sure to employ techniques to mitigate occlusion. b. Compute the 25%, 50%, and 75% percentiles of the data for the high school science teachers and for high school English teachers. c. Comment on the differences in the number of hours worked per week for high school science teachers and English teachers.

Solution: a. An example of a strip chart with hollow dots and jittering follows.

b. The percentiles are given in the following table:

25% 50% 75%

Science Percentile 50 53 55.25

English Percentile 42.75 47 52

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

c. At all three percentiles, we observe science teachers work more hours per week than English teachers. However, there is more variation among English teachers than among science teachers, which can be seen in the strip chart as well as by comparing the IQR of the science teachers to the IQR of English teachers. The IQR of science teachers is 55.25 – 50 = 5.25 hours and the IQR of English teachers is 52 – 42.75 = 9.25 hours.

22. Average Tax Payment Error. A sample of 10,001 Federal income tax returns with errors has been collected and the amount of payment error for each is provided in the file fedtaxerrors. A positive value indicates the taxpayer underpaid and a negative value indicates that the taxpayer overpaid. LO 5, 7 a. What is the sample mean tax payment error made on these erroneous Federal income tax payments? b. What is the sample standard deviation in payment error amount? c. What is the margin of error for a 95% confidence interval on the mean payment error amount? d. Construct a column chart displaying the sample mean tax payment error with error bars depicting a 95% confidence interval. e. Can we conclude with 95% confidence that the mean tax payment error is positive (a taxpayer underpayment)?

Solution: a. $327 b. $12,318 c. $241 d.

e. Because the 95% confidence interval lies above $0, we can conclude with 95% confidence that the mean tax payment error is positive (an underpayment by the taxpayer).

23. Proportion of Tax Underpayment. A sample of 10,001 Federal income tax returns with errors has been collected and the amount of payment error for each is provided in the file fedtaxerrors. A positive value indicates the taxpayer underpaid and a negative value indicates that the taxpayer overpaid. LO 7 a. What is the sample proportion of erroneous income tax returns that correspond to tax underpayments? b. What is the margin of error for a 95% confidence interval on the proportion of erroneous tax returns corresponding to tax underpayments?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

c. Construct a column chart displaying the sample proportion of tax underpayments with error bars depicting a 95% confidence interval. Construct the chart to explicitly compare the sample proportion and confidence interval to a 50% proportion benchmark. d. Can we conclude with 95% confidence that more than 50% of tax payment errors correspond to tax underpayments?

Solution: a. 0.508 b. 0.010 c.

d. Because the 95% confidence interval contains 50%, we cannot conclude with 95% confidence that more than 50% of erroneous tax returns correspond to tax underpayments.

24. Restaurant Franchising (Revisited). In this problem we revisit the simple linear regression model from Problem 13 for predicting a restaurant’s quarterly sales with the size of the nearby student population. The chart and associated data are contained in the file restaurant_chart. LO 8 a. Modify the chart to convey the uncertainty related to the predictions corresponding to the simple linear regression model. b. For approximately what value of student population is the regression model the most accurate?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 5: Visualizing Variability

Solution: a.

b. The regression model is most accurate for predictions near the mean student population, which for this data is 14,000 students.

25. Forecasting Stock Price (Revisited). In this problem we revisit the chart from Problem 14 displaying historical price and forecasted price for a stock. The chart and associated data are contained in the file daytrading_chart. LO 8 a. Modify the chart to convey the uncertainty related to the forecasts of the stock prices in future days. b. What can be said about the prediction of the stock price one day in the future versus the prediction of the stock price ten days in the future?

Solution: a.

b. As the increasing width of the prediction intervals suggests, the further into the future one tries to predict the stock price, the more uncertain one is about this prediction.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 6: EXPLORING DATA VISUALLY

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1 CONCEPTUAL ............................................................................................................................. 1 APPLICATIONS........................................................................................................................... 8

END OF SECTION PROBLEM SOLUTIONS CONCEPTUAL 1.

Choosing Appropriate Chart. A fitness lab has conducted an experiment in which 100 participants engage in a 30-minute period of high-intensity interval training (HIIT) and then are asked about their perceived level of exertion. They must select an answer from 1 to 4, where 1 = “did not feel challenged”; 2 = “broke a sweat but could have been pushed more”; 3 = “felt challenged but not overwhelmed”; and 4 = “extremely fatigued.” In addition, each participant’s body fat percentage is recorded. The following table displays a portion of the data from the experiment. LO 4 Participant 1 2 3 4 5

Body Fat Percentage 27 31 24 21 14

Exertion Level 3 4 1 2 4

What is a good way to show how body fat percentage is related to exertion level? i. Scatter chart depicting relationship between body fat percentage and exertion level ii. Side-by-side box and whisker plots of the distribution of body fat percentage for participants at each exertion level iii. Clustered column chart of body fat percentage with different colored columns for each exertion level iv. Sparklines on data unstacked so columns correspond to different exertion levels Solution: ii 2. Performance Evaluation. Kiwi Analytics is assessing two different training programs for its consulting employees. One group of 50 employees used training method A for varying numbers of hours and another group of 50 employees used training method B for varying numbers of hours. Then these employees were evaluated based on their performance in

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1

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

job-related tasks. The resulting data from this experiment is displayed in the following two scatter charts. LO 6

Which of the following are accurate statements based on these data? Select all that apply. i. Training method A and training method B are equally effective at improving evaluation scores. ii. Training method A is more effective than training method B because the observations in the first scatter chart exhibit less variability around the linear trendline than the observations in the second scatter chart. iii. Correlation does not imply causation and therefore there is no meaningful conclusion from these charts. iv. The strength of the linear relationship between hours of training and evaluation score is the same for both training method A and training method B. Solution: iv

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

3. Correlation Analysis of Wide Data. Helen Wagner, a marketing analyst for Meredith Corporation, is examining a data set based on market research of potential patrons of a new social-media-based e-magazine. The data set has dozens of quantitative variables measuring characteristics such as patron income, age, daily hours spent on social media, money spent based on banner ads on websites, etc.

Helen is interested in exploring the association between these variables. What visualization would you recommend? LO 5 i. Scatter-chart matrix ii. Table lens iii. Heatmap iv. Choropleth map Solution: ii 4. Tailored Delivery. Bravman Clothing sells high-end clothing products and is launching a service in which they use a same-day courier service to deliver purchases that customers have made by working with one of their personal stylists on the phone. In a pilot study, Bravman collected 25 observations consisting of the wait time the customer experienced during the order process, the customer’s purchase amount, the customer’s age, and the customer’s credit score. The data for these 25 observations was used to construct the following scatter-chart matrix. LO 6

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Which of the following statements most accurately describes the insight from the scatterchart matrix? i. Purchase amount, customer age, and credit score have pairwise positive relationships with each other. ii. Wait time has a nonlinear relationship with purchase amount. iii. Wait time is negatively related to customer age. iv. None of the variables appear to be highly correlated with each other.

Solution: i 5. Wage Income Over Lifetime. The Pew Research Center is a nonpartisan think tank that gathers information on social issues and demographic trends. It has conducted a longitudinal study in which they collected the wage income of finance professionals at various points in their lives. After accounting for inflation, the data from this study was used to create the following chart. LO 5

What is the best way to visually emphasize the apparent relationship between wage income and age in this chart? i. Add a linear trendline to the chart. ii. Compute the correlation between the two variables and display this on the chart. iii. Remove the fill color of the data points. iv. Add a nonlinear trendline to the chart.

Solution: iv 6. Wage Income Over Lifetime. Using data from a longitudinal study that collected wage income of finance professionals at various points in their lives, an analyst has constructed the following scatter chart and placed a linear trendline on the data. LO 5

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

What is a reasonable conclusion from this chart? i. There is no relationship between a person’s age and their wage income. ii. A person’s age and wage income do not appear to be linearly related, but there does appear to be a nonlinear relationship between these two variables. iii. A scatter chart is not the best way to view these data because they were collected over time and therefore a line chart should be used. iv. None of the variables appear to be highly correlated with each other.

Solution: ii 7. Types of Missing Data. Label each of the following descriptions based on the type of missing data being described: missing completely at random (MCAR), missing at random (MAR), or missing not at random (MNAR). LO 7 a. A survey is conducted that asks a sample of people their age, highest level of education completed, and preference of political party. The results indicate that many entries for highest level of education completed are missing, and that respondents were more likely to omit this response if they had a high school education or less. b. An economic study is conducted asking people to report their profession, job title, and city of residence. Approximately 10% of the responses for job title are missing, and it is observed that men are less likely to provide their job title than women. c. Students at a local college are given a survey to collect data on their study habits and preferred learning styles. Students complete the survey by filling out a Scantron form on which they fill in circles to specific multiple-choice questions. Due to Scantronreading errors, five % of the question responses are not able to be read correctly and so are recorded as missing. d. A clinical study is being done to judge the efficacy of a new drug in reducing a patient’s high blood pressure. Each month study participants must each undergo a stress test where they run on a treadmill at maximum effort for 90 seconds, after which the patient’s blood pressure is recorded. However, each patient is screened prior to the stress test and if their resting blood pressure is too high, they do not complete the stress test and the blood pressure reading for that patient is missing.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution: a. MNAR b. MAR c. MCAR d. MNAR 8. Patterns in Missing Data. Dr. Drake Ramoray is reviewing a patient database and has noticed that there are some missing data entries. As shown in the table below, he has highlighted these missing entries as black cells. LO 7

Examine the pattern in this missing data. Which of the following classifications seems most appropriate? i. Missing not at random illegitimately ii. Missing at random iii. Legitimately missing data iv. Missing completely at random Solution: iii 9. Smartphone Sales. A manufacturer has collected the sales data for the past four years.

How should the analyst team visualize this data if they are interested in exploring sales patterns over time? LO 8 i. Pie chart breaking down sales by year ii. Heatmap to emphasize the times of the year which sales peak iii. A set of line charts that aggregate data at different time intervals: by year, by quarter, and by month iv. Radar chart to represent the cyclical nature of the business year Solution: iii 10. High-Speed Rail Passengers. Darcy Sears is a manager of a high-speed rail service between two major metro areas. Darcy is analyzing three years (36 months) of data on the number of passengers who ride the high-speed train and has created the following chart. LO 8

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Based on her experience with the rail service, Darcy believes there is a seasonal pattern in amount of passenger traffic on the high-speed train. However, Darcy is disappointed that her chart does not clearly display seasonality. How should Darcy better visualize a seasonal pattern in the data? i. Create a different data series for each year consisting of 12 monthly observations and plot these three separate lines on a new chart with the month labels January through December on the horizontal axis. ii. Aggregate the monthly observations into yearly observations and plot the data on a new chart with Year on the horizontal axis. iii. Add a linear trendline to the chart above. iv. Add a moving average with a period equal to the length of the seasonal pattern.

Solution: i 11. Comparing Moving Averages. What is the effect of decreasing the number of periods in a moving average? LO 8 i. The moving average trendline becomes smoother and less sensitive to fluctuations in the values of the data. ii. The value of the moving average always decreases. iii. The moving average trendline becomes more jagged and more responsive to recent changes in the values of the data. iv. There is no effect as the moving average depends on the seasonal pattern.

Solution: iii 12. Omaha Steaks. As part of a marketing campaign harkening on its company history based on Nebraska’s beef industry, Omaha Steaks wants to create a visualization displaying the state’s geographic distribution of beef cattle. Using data on the number of beef cattle in each county in Nebraska, the following choropleth map was created. LO 9

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Which of the following choices best summarizes the strengths and weaknesses of this visualization? i. The choropleth map does a good job of depicting the geographic distribution of beef cattle in the state of Nebraska. However, the color shading does not provide a distinct enough contrast to identify the counties with the most beef cattle. ii. The choropleth map does a good job indicating the counties containing the most cows in absolute terms. However, there is a tendency for the largest counties to have the most cattle primarily due to their land area, and this can convey a false differentiation in the density of cows in adjacent counties. iii. The use of color clearly shows which counties contain the most beef cattle. However, the large variance in the size of the counties makes it difficult to extract insight from the visualization for all counties. iv. I, ii, and iii are all accurate comments.

Solution: ii APPLICATIONS 13. Tax Data by County. The file taxdata contains information from federal tax returns filed in 2007 for all counties in the United States (3,142 counties in total). Create an Excel Table based on these data. Using Excel Table functionality, answer the following questions. LO 1 a. Which county had the largest total adjusted gross income in the state of Texas? b. Which county had the largest average adjusted gross income in the state of Texas?

Solution: a. Filtering the data on TX in the State Abbreviation column and sorting by Adjusted Gross Income, we discover that Harris County had the largest total adjusted gross income in Texas.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

b. Creating a new column called Average AGI computed by dividing Adjusted Gross Income by Total Number of Tax Returns, we discover that Kendall County had the largest average adjusted gross income in Texas.

14. More Univariate Analysis of EJB Data. In the EJB example discussed within the chapter, univariate analysis was demonstrated on some of the variables. We continue this analysis in this problem. LO 2 a. Using a PivotChart, construct the relative frequency distribution of records over the values of the Category variable. Describe your findings. b. Using a PivotChart, construct the relative frequency distribution of records over the values of the New Customer variable. In the PivotTable, relabel a “No” value for New Customer as “Existing” and a “Yes” value as “New.” Describe your findings.

Solution: a. Juices make up 55.17% of total orders and smoothies make up 44.83% of total orders.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

b. Existing customers make up 79.26% of all orders and new customers represent 20.74% of all orders.

15. Missing Data for Product Satisfaction Rating. To understand the implications of missing data, we must explore the patterns associated the missing entries for the Product Satisfaction Rating variable in the EJB data used within the chapter. LO 2, 7 a. Construct the relative frequency distribution of records over the values of the Product Satisfaction Rating variable. What percentage of records are missing a value of Product Satisfaction Rating? b. Considering only records that report values of Product Satisfaction Rating, construct the relative frequency distribution of records over the different flavors. c. Considering records that are missing values of Product Satisfaction Rating, construct the relative frequency distribution of records over the different flavors. d. Compare the distributions in part (b) and part (c). What does this comparison suggest?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution: a. 53.21% of orders are missing a value for Product Satisfaction Rating.

b.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

c.

d. The percentage of orders missing a product satisfaction rating that involve orange is 18.50%, but the percentage of orders reporting a product satisfaction rating that involve orange is only 12.87%. This suggests that the tendency of an order to be missing a product satisfaction rating is affected by whether the order involves the orange flavor.

16. Business Graduate Salaries. In the file majorsalary, data have been collected from 111 College of Business graduates on their monthly starting salaries. The graduates include students majoring in management, finance, accounting, information systems, and marketing. LO 2, 3 a. Create a PivotChart to display the number of graduates in each major. Which major has the largest number of graduates? b. Create a PivotChart to display the average monthly starting salary for students in each major. Which major has the highest average starting monthly salary?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution: a. Accounting has the largest number of graduates.

b. Accounting has the highest average monthly salary.

17. Federally Insured Bank Failures. The file fdic contains data on failures of federally insured banks between 2000 and 2012. Create a PivotChart to display a column chart that shows the total number of bank closings in each year from 2000 through 2012 in the state of Florida. Describe the pattern observed in the chart. LO 3

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution: Bank closings swelled to a peak in 2010 and subsided to pre-2009 levels by 2012.

18. Market Capitalization and Profit. The file fortune500 contains data for profits and market capitalizations from a recent sample of firms in the Fortune 500. Prepare a scatter chart to show the relationship between the variables Market Capitalization and Profit in which Market Capitalization is on the vertical axis and Profit is on the horizontal axis. Create a trendline for the relationship between Market Capitalization and Profit. What does the trendline indicate about this relationship? LO 5 Solution: There appears to be a positive linear relationship between profits and market capitalization. As profit increases, market capitalization also increases.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

19. Market Capitalization and Profit By Sector. The file fortune500sector contains data on the profits, market capitalizations, and industry sector for a recent sample of firms in the Fortune 500. LO 5 a. Differentiating observations by using a different color for each industry sector, prepare a scatter chart to show the relationship between the variables Market Capitalization and Profit in which Market Capitalization is on the vertical axis and Profit is on the horizontal axis. b. Emphasize the relationship between Market Capitalization and Profit within the healthcare sector by formatting all other sectors with data points in gray with no fill.

Create a trendline based only on the observations in the healthcare sector. What does the trendline indicate about this relationship between Market Capitalization and Profit within the healthcare sector?

Solution: a.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

b. There appears to be a positive linear relationship between profits and market capitalization within the healthcare sector. As profit increases, market capitalization also increases.

20. Table Lens on Customer Data. Bravman Clothing sells high-end clothing products and is launching a service in which they use a same-day courier service to deliver purchases that customers have made by working with one of their personal stylists on the phone. In a pilot study, Bravman collected 25 observations consisting of the wait time the customer experienced during the order process, the customer’s purchase amount, the customer’s age, and the customer’s credit score. The file bravman contains the data for these 25 observations. LO 5 a. Construct a table lens on this data sorted in decreasing order with respect to the values of the Purchase Amount variable. b. Summarize the relationships between Purchase Amount and the other three variables.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution: a.

b. From the table lens, we see there appears to be no relationship between purchase amount and wait time. There appears to a slight positive correlation between purchase amount and customer age, and between purchase amount and credit score.

21. Missing Data in Marketing Survey. The file surveyresults contains the responses from a marketing survey: 108 individuals responded to the survey of 10 questions. Respondents provided answers of 1, 2, 3, 4, or 5 to each question, corresponding to the overall satisfaction on 10 different dimensions of quality. However, not all respondents answered every question. LO 7 a. To highlight the missing data values, shade the empty cells in black. b. For each question, which respondents did not provide answers? Which question has the highest nonresponse rate?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution: a. The highlighted missing values for the first 15 respondents is shown below.

b. Question 1: Respondents 4, 18 Question 2: Respondents 8, 74, 87, 100 Question 3: Respondents 3, 4, 78, 101 Question 4: Respondents 6, 15, 23, 76, 82, 106 Question 5: None Question 6: Respondents 5, 70, 86 Question 7: Respondents 34, 81 Question 8: Respondents 82, 96 Question 9: Respondents 23, 50 Question 10: Respondents 15, 37, 45 Question 4 has the highest nonresponse rate with six respondents not providing answers.

22. Smartphone Sales. The file pixel contains data on the monthly sales revenue for a smartphone manufacturer. LO 8 a. Create a line chart to depict the sales time series at the annual level. b. Create a line chart to depict the sales time series at the quarterly level. c. Create a line chart to depict the sales time series at the monthly level. d. What insight do each of these three views provide?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution: a.

b.

c.

d. Plotting smartphone sales on an annual basis displays the longer-term upward trend over the past four years. Plotting smartphone sales on a quarterly basis reveals the seasonal pattern for this product. Plotting smartphone sales on a monthly basis emphasizes the amount of short-term variability reinforcing to management that month-to-month fluctuations should not necessarily cause an overreaction.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

23. Umbrella Sales. The file umbrella contains data on the quarterly sales revenue for a manufacturer of umbrellas and other weather-resistant gear. LO 8 a. Create a line chart for the sales time series data. Add a four-period moving average to the chart to smooth the data. b. To investigate the possibility of seasonality on a quarterly basis, plot the data as a collection of five data series (one for each year). From this visualization, do you observe any indication of seasonality? If so, describe it.

Solution:

a.

b. Umbrella sales annually peak in Quarter II and hit an annual low in Quarter IV.

24. Analysis of Scoring in the NFL. The file scoringnfl contains the points scored by each National Football League team for 10 seasons. LO 1, 8 a. NFL leadership is interested in seeing how the distribution of scoring across the league has changed over these 10 seasons. Construct a single chart that allows the audience to make these comparisons. Provide a thorough discussion of the distribution of scoring in the league over this decade. b. NFL leadership is also interested in the temporal patterns in scoring for individual teams. Unstack the data and use sparklines to show how scoring for each team has changed over these 10 seasons. List a team with a strong upward trend over these 10 seasons. List a team with a strong downward trend over these 10 seasons.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

Solution: a. For most seasons, the scoring distribution of NFL teams is fairly symmetric with the mean and median of the league being similar. There have been two high-scoring outlier teams (the Green Bay Packers in 2011 and the Denver Broncos in 2013). In 2013, the scoring distribution was negatively skewed. In 2018, the scoring distribution was positively skewed. The variability of the league’s scoring distribution fluctuates substantially from season to season. For example, in 2012 there was a wide range in the team scoring, but in 2013 the teams’ scoring was more similar (except for the outlier team).

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

b. Very few teams demonstrate a stable trend either upward or downward over these 10 seasons, suggesting a high degree in season-to-season variability in a team’s scoring ability.

Teams with a detectable downward trend over these 10 seasons: Denver Broncos and New England Patriots Team with a detectable upward trend over these 10 seasons: Kansas City Chiefs

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 6: Exploring Data Visually

25. Omaha Steaks (Revisited). In this problem, we revisit the data from Problem 12. As part of a marketing campaign harkening on its company history based on Nebraska’s beef industry, Omaha Steaks wants to create a visualization displaying the state’s geographic distribution of beef cattle. Data on the number of beef cattle in each county in Nebraska and the size of each county are contained in the file nebraskabeef. Create a choropleth map that shades each county in Nebraska relative to the density of beef cattle (as measured by head per square mile). Compare this visualization to the choropleth map in Problem 12 and describe the strengths and weaknesses. LO 9 Solution: The choropleth map based on cattle density does a good job of conveying the concentrations of beef cattle and changes between adjacent counties are generally much more gradual, which reflects reality. This choropleth map does not convey the total beef cattle numbers of a county well, however, and small counties may have high beef cattle density, but a relatively small absolute number of beef cattle.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 7: EXPLAINING VISUALLY TO INFLUENCE WITH DATA

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1 CONCEPTUAL ............................................................................................................................. 1 APPLICATIONS........................................................................................................................... 9

END OF SECTION PROBLEM SOLUTIONS CONCEPTUAL 1.

Understanding Needs of the Audience. For each of the following audiences, indicate whether the audience members are more likely to need a high-level understanding or a detailed understanding from a data visualization. LO 1 a. You are presenting the results of a marketing segmentation study to a group of data scientists and the company’s Chief Analytics Officer (CAO). The market segmentation study is designed to determine customer groups for the company to better target the company’s market to specific customer segments. There are several different algorithms that can be used to perform market segmentation, and the goal of the data visualization is to get feedback from the data scientists on the different algorithms and help the CAO make a decision on which algorithm should be used. b. You are presenting the results of a fundraising analysis to the Board of Directors for a large nonprofit company. The fundraising analysis is designed to suggest some additional approaches for increasing the propensity for donors to financially contribute to the organization. The Board of Directors provides general oversight for the nonprofit, but it is not involved in day-to-day decision making for the company. The board is composed of people who are known to be philanthropic and have considerable personal resources, but they have little background or expertise in analytics. c. You are preparing a data visualization that will accompany a public-relations media release for a project that you recently completed for a startup company that does political polling and analysis. The project used data collected from likely voters in an upcoming election, and the goal was to determine the issues that are most important in terms of influencing who these voters will choose in the next election. The media release will be sent to a wide range of possible outlets including local television networks and magazines. The goal of the public-relations release is to generate publicity for the startup company and make the general public aware of the type of work this startup company does.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Solution: a. Detailed understanding b. High-level understanding c. High-level understanding 2. Rainfall Amounts by Location. Consider the following two possible data visualizations that display the results of an analysis of data collected by the meteorology department of a local university. The data collected are based on the monthly amount of rainfall received at 10 different locations (labeled as Locations A–J) over the last two years. LO 1

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

a. Which of these two data visualizations (box and whisker chart or column chart) would be most appropriate for an audience that has a high comfort level with analytics and would like to understand the variability in monthly rainfall amounts at the 10 locations? Why? b. Which location has the highest variability in monthly rainfall amounts? c. Which location has the lowest variability in monthly rainfall amounts?

Solution: a. The box and whisker chart. Because the column chart shows only average values for each location, it does not provide any information on the variability of rainfall amounts for locations. b. From what is shown in the box and whisker chart, Location I appears to have the highest variability in monthly rainfall amounts because the box and whisker chart for this location is widest. c. Location B appears to have the lowest variability in monthly rainfall amounts because the box and whisker chart for this location is narrowest.

3. Expense Report Table. The following table shows a monthly expense report summary for an academic department at a community college located in Bethesda, Maryland. LO 1 Expense Category

Expense Amount ($)

Office Supplies

32.92

AV & Media Parts/Sup

78.90

Computing Expenses

348.71

Computer Supplies

220.39

Printer Supplies

21.55

AV Planning & Consul

1,248.50

Video Conferencing

29.98

Meeting/Seminar/Event

149.33

Refreshments & Meals

4,899.03

Travel

5,256.30

Adv & Development

3,983.75

Marketing/Promotion

3,000.00

Postage & Delivery

14.88

Memberships & Dues

3,600.00

Print/Dupl/Graphics

846.47

Parking (NonTravel)

861.50

Credit Card Process Fee

2,883.51

Services

4,136.80

Repair/Maintenance Electric

75.00 489.00

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Is this data visualization better suited for an audience that needs detailed insights or high-level insights?

Solution: Detailed Insights 4. Chart to Provide Sense of Scale for Large Numerical Values. Which of the following chart types is best used to provide a sense of scale for large numerical values in a data visualization? LO 4 i. Clustered column chart ii. Box and whisker chart iii. Dot matrix chart iv. Slope chart Solution: iii.

5. Chart to Show Changes Over Time of Multiple Entities. Which of the following chart types can be used to easily show changes to multiple entities over time? LO 3 i. Clustered column chart ii. Box and whisker chart iii. Dot matrix chart iv. Slope chart Solution: iv 6. Ethos, Logos, and Pathos. Match each of the following terms with their correct explanation.

LO 7 TERM Ethos Logos Pathos

EXPLANATION Connecting to an audience based on logic Connecting to an audience based on emotion Connecting to an audience by establishing credibility

Solution: TERM Ethos Logos Pathos

EXPLANATION Connecting to an audience based on logic Connecting to an audience based on emotion Connecting to an audience by establishing credibility

7. Examples of Ethos, Logos, and Pathos. For each of the following examples, indicate whether it is an example of connecting with an audience using ethos, logos, or pathos. LO 7 a. Providing references to all raw data used to create your data visualizations so that the audience understands that the data come from reputable sources. b. Including pictures of specific types of people affected by the data represented in your data visualization. c. Explicitly listing limiting assumptions that were made in creating a particular data visualization. d. Using a clear reasoning to connect your data visualization to a recommended action for the decision maker. e. Creating context for large numerical values used in a data visualization so the audience has some relative reference to understand these values.

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Solution: a. Ethos b. Pathos c. Ethos d. Logos e. Pathos 8. Providing a Storytelling Structure for a Presentation. Which of the following provides a suggested structure for a story to be used for a presentation? LO 8 i. Freytag’s Pyramid ii. Rhetorical triangle iii. Preattentive attributes iv. Ethos, logos, and pathos Solution: i.

9. Elements of Freytag’s Pyramid. Match each of the following elements from Freytag’s Pyramid with the correct description of the characteristics of that element. LO 8 FREYTAG’S PYRAMID ELEMENT Introduction Rising Action Climax Falling Action Conclusion

DESCRIPTION Highlights the major conflict in the story and presents the outcome of the conflict Presents the end of the story Explains the obstacles that are facing the protagonist Connects the resolution of the conflict to how the story will end Presents the background information for the story and describes the protagonist

Solution: FREYTAG’S PYRAMID ELEMENT Introduction Rising Action Climax Falling Action Conclusion

DESCRIPTION Highlights the major conflict in the story and presents the outcome of the conflict Presents the end of the story Explains the obstacles that are facing the protagonist Connects the resolution of the conflict to how the story will end Presents the background information for the story and describes the protagonist

10. BAN and Preattentive Attributes. Using a BAN in a data visualization illustrates the use of which preattentive attribute? LO 4 i. ii. iii. iv.

Size Color Shape Motion

Solution: i

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

11. Unemployment Rates for New England States. The line chart below shows seasonally adjusted unemployment rates between 2010 and 2020 for states located in the New England region of the United States. The designer of this chart wants the audience to be able to easily compare the unemployment rates during this time frame for Massachusetts to the other states in the New England region. LO 6

Source: https://www.bls.gov/charts/state-employment-and-unemployment/state-unemploymentrates-animated.htm

How can the designer of this data visualization use the preattentive attribute of color to make this comparison easier for the audience?

Solution: The designer can use the preattentive attribute of color by using a single color (for example, gray) for the lines corresponding to unemployment rates in all New England states other than Massachusetts and then a different color (for example, red) for the line corresponding to unemployment rates in Massachusetts.

12. Lack of Access to Improved Drinking Water. Improved drinking water sources are defined as drinking water sources that are protected from outside contamination. According to the World Health Organization, 663 million people around the world lack access to sources of improved drinking water, which puts them at high risk for infection and illness. The bar chart below shows the number of people in each region that are estimated by the World Health Organization to lack access to improved drinking water sources. LO 2

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Source: Data from World Health Organization: https://apps.who.int/iris/bitstream/handle/10665/177752 /9789241509145_eng.pdf;jsessionid=D7AEF25BD6C2002814352BD93FCD5607?sequence=1

Which of the following suggestions would improve this chart in terms of helping the audience empathize with the data? (Select all that are appropriate.) i. Add a picture showing people who lack access to improved drinking water sources. ii. Color each bar differently to create more excitement for the audience. iii. Use a dot matrix chart instead of a bar chart to give the audience a better understanding of the magnitudes of these numerical values. iv. Use a pie chart instead of a bar chart because pie charts create more empathy than bar charts due to use of preattentive attribute of shape. v. Use a three-dimensional (3D) bar chart because the depth dimension of a 3D chart moves an audience to feel more empathy.

Solution: i., iii.

13. Sprouts Learning Academy Math Enrichment Program. Sprouts Learning Academy helps prepare students for standardized tests in math for children in the second- through fifthgrade levels. Sprouts assesses each child by giving them a pretest when they start their math enrichment academy program and then again at the conclusion of the academy program. The test results are measured in percentiles compared to all other students taking similar tests. The clustered column chart below shows the results of these pre- and postacademy tests for each grade level. The designer of this chart would like to communicate to the audience about how well the math enrichment program is doing in improving the performance of the students on this standardized test at each grade level. LO 5

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Which type of chart could be used to better tell the story about how well the math enrichment program is doing in improving performance on this standardized test? i. Pie chart ii. Slope chart iii. Dot matrix chart iv. Box and whisker chart Solution: ii.

14. Storyboard Materials. Which of the following are recommended tools for creating a storyboard to help plan the structure of a presentation? (Select all that apply.) LO 9 i. Microsoft Excel ii. A calculator iii. Sticky notes iv. Microsoft PowerPoint Solution: iii., iv.

15. Low-Tech versus High-Tech Storyboards. Which of the following is the foremost advantage of using a low-tech method versus a high-tech method for creating a storyboard to be used for designing a presentation? LO 9 i. Low-tech methods remove the temptation of being distracted with creating final slide designs during the storyboarding process so you can concentrate on creating the structure of the story. ii. Low-tech methods are much faster to implement than high-tech methods. iii. Low-tech methods make it easier to turn the finished storyboard into the final slides for the presentation. iv. Low-tech methods make it much easier to create the final versions of extremely sophisticated data visualizations to be used in the final presentation.

Solution: i.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

16. Storyboarding Goal. Which of the following best describes the goal of the storyboarding process? LO 9 i. Determine how to use design elements such as preattentive attributes in your data visualizations to best tell your story. ii. Create a visual outline of the structure of your presentation. iii. Put the finishing touches on a presentation by focusing on the format and design of the final data visualizations. iv. Provide an opportunity to examine the data to be used to create the data visualizations to create the most effective charts for your audience.

Solution: ii.

APPLICATIONS 17. Unemployment Rates for New England States (Revisited). In this problem, we revisit the chart shown in Problem 11 showing seasonally adjusted unemployment rates for states in the New England region. Use the preattentive attribute of color to modify this chart so that the audience can easily compare the unemployment rates during this time frame for Massachusetts to the other states in the New England region. LO 6 Solution:

Note that we have also changed the chart title in this modified chart to give it a more descriptive title to match the story to be told using the chart.

18. Lack of Access to Improved Drinking Water (Revisited). In this problem, we revisit the chart shown in Problem 12 showing the number of people without access to improved drinking water sources by region. LO 4, 6 a. Approximately 663 million people do not have access to improved drinking water sources around the world. Add a BAN to the bar chart in the file drinkingwater_chart

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

so that the total number of people in the world who do not have access to improved drinking water sources is emphasized in this chart. b. To help create empathy with the data for the audience, create a dot matrix chart to represent the data in the file drinkingwater_chart. Use ● = 1 million people for your dot matrix chart. (Hint: To represent 663 million people who lack access to improved drinking water resources, you will need a matrix that contains 663 ●. You can create this by using a 25 x 26 matrix and then adding an additional partial row of 13 ●. ) c. Differentiate the colors of the ● based on the region of the world. Include a legend on your modified dot matrix chart. d. The population of the United States is approximately 330 million people. To help give the audience an even better sense of scale for the number of people around the world who lack access to improved drinking water, use the Gestalt principle of enclosure by using the Fill Color function in Excel to shade the cells containing the number of ● that correspond to the population of the United States and label this on your chart.

Solution: a.

Number of People Without Access to Improved Drinking Water Sources Region

663,000,000

Other

People Around The World Lack Access to Improved Drinking Water Sources

South-eastern Asia

Eastern Asia

Southern Asia

Sub-saharan Africa

0

50

100

150

200

250

300

350

Number of People (millions)

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

b.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

c.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

d.

19. Sprouts Learning Academy Math Enrichment Program (Revisited). In this problem we revisit the chart shown in Problem 13 for standardized test scores from the pre-mathenrichment program and post-math-enrichment program at Sprouts Learning Academy.

LO 5, 6 a. Create a slope chart for the data in the file sproutslearning_chart that compares the pre- and post-math-enrichment program standardized test scores for secondthrough fifth-grade levels. b. Test scores have increased for all grade levels between pre- and post-mathenrichment program tests. However, test scores for fourth-grade level have less difference than the test scores of second-, third-, and fifth-grade levels. Use the preattentive attribute of color to emphasize the difference in the results for fourthgrade level compared to second-, third-, and fifth-grade levels.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Solution: a.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

b.

20. Engineering Graduate Salaries at Empire State University. Empire State University (ESU) collects salary data for its engineering college graduates. ESU collects data on starting salaries for its graduates and then again five years post-graduation. The table below shows the median starting salaries and median salaries five years post-graduation by engineering major. Create a slope chart to display these data. LO 5 Engineering Major Chemical Civil Computer Electrical Industrial Mechanical

Starting 72,500 61,000 68,400 64,800 57,400 62,900

Salaries ($) 5 Years Post Graduation 91,400 70,300 83,600 87,400 74,000 77,100

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Solution:

21. Measuring Viral RNA Load. Viral RNA load measures the amount of virus in a specified volume of bodily fluid. When someone is sick due to a viral infection, the virus replicates rapidly in the body and can be measured based on the viral RNA load. Consider four possible virus vaccines that are being tested in clinical trials: Vaccines A, B, C, and D. Each vaccine is given to a group of people and the viral RNA load of each patient is measured.

The study also includes a Control group of patients who receive only a placebo vaccine.

The epidemiologists running these vaccine trials would like to present the results of the studies using a box and whisker chart for an audience of clinicians who are familiar with how to interpret box and whisker charts. The epidemiologists would like to emphasize the results for Vaccine C compared to the results for the Control group. Modify the box and whisker chart found in the file virus_chart using the preattentive attribute of color to emphasize the results of Vaccine C and the Control group to make it easier for the audience to make the comparison between these data. LO 6

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Solution:

22. Defining Freytag’s Pyramid Structure for a Story. Think of one of your favorite books, movies, or plays. Divide up the story that is told in this book, movie, or play according to the elements outlined in Freytag’s Pyramid: Introduction, Rising Action, Climax, Falling Action, Conclusion. For each element briefly describe what part of the story is included in this element and how it fits into the defined element. LO 8 Solution: There are many possible answers here. Students should clearly identify elements of the story such as establishing the setting and introducing the protagonist in the introduction, setting up the conflict to be resolved in the climax, and discussing how the story ends in the conclusion.

23. Storyboard for Reducing Waiting Time at General Hospital. The Division of Performance Improvement and Analytics at General Hospital has been working on a four-month project to provide recommendations for reducing the waiting time experienced by patients who arrive to its Pediatrics Health Care Wing that provides for prescheduled clinical services such as checkups and wellness visits. The project began with an intensive six-week data collection effort that measured the waiting time for patients as well as the patient satisfaction with their visit and any required follow-up visits. The next four weeks were spent cleaning the data and matching the data with existing patient and healthcare provider data from the hospital’s IT system. The remainder of the time was spent analyzing the data, discussing findings with the clinicians, and formulating final recommendations.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

The team is now ready to present its findings and recommendations to the senior leadership of the hospital, including the hospital’s Chief Operating Officer (COO) who has final decision-making power to decide which, if any, recommendations to be followed.

Some of the interesting findings identified by the team from the Division of Performance Improvement and Analytics include the following: • Patients who were scheduled in the first or second appointment of the day experienced an average waiting time of 5.8 minutes. Patients who were scheduled for the next-to-last or last appointment of the day experienced an average waiting time of 42.3 minutes.

• Patients who responded to a reminder call about their appointment had a no-show rate (meaning they did not show up at the scheduled time of their appointment) of 8.5%. Patients who did not respond to a reminder call about their appointment had a no-show rate of 19.3%.

• Patient no-show rates were slightly higher in the afternoon than in the morning and higher on Fridays than any other weekday.

• Seventy-four percent of patients who received a text reminder responded to the reminder while only 51% of patients who received a phone call responded to the reminder.

• When patients did not show up for their scheduled appointment time, patients who did not have a prescheduled appointment were often given priority to fill this slot. However, these patients required an average appointment duration that was 1.7 times as long as prescheduled patients because they had to complete additional tasks such as filling out medical history forms.

• There was substantial variability in the waiting times experienced by patients across different clinicians. Patients waiting to see Dr. Martinez had the highest average waiting times, which were 1.5 times as long as the average waiting times for Dr. Ahuja, whose patients had the shortest average waiting times.

• Patient waiting times are highly correlated with their satisfaction-survey scores.

Patients who waited longer had substantially lower patient-satisfaction scores.

• Patients seen in the morning were 17% more likely to have a follow-up visit scheduled than those seen in the afternoon.

Based on these findings, the team would like to make the following recommendations: • All patients should receive a text message in addition to a phone call about an upcoming appointment.

• A new team should be created to examine the creation of standards for pediatric patient checkups and wellness visits to (1) reduce the variability experienced by patients waiting to see different clinicians; (2) examine the cause of why patients seen in the morning are scheduled for follow-up visits more often than patients seen in the afternoon.

• Allow more time between scheduled patient visits in the afternoon than in the morning to prevent long waits for patients arriving in the afternoon.

Create a storyboard to outline the structure of the presentation for this audience of senior hospital executives including the COO. Make sure that your storyboard clearly defines the protagonist in your story and provides sufficient detail that it could be used to create a final presentation. LO 9, 10

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 7: Explaining Visually to Influence with Data

Solution: There are many possible answers here. Students could create a storyboard using either a clinician or a patient as the protagonist. To best connect with the audience the storyboard should contain specific elements and attempt to connect with the audience using ethos, logos, and pathos. The storyboard should provide enough detail that the structure of the story is clear and could be used to develop a final presentation.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 8: DATA DASHBOARDS

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1 CONCEPTUAL ............................................................................................................................. 1 APPLICATIONS........................................................................................................................... 5

END OF SECTION PROBLEM SOLUTIONS CONCEPTUAL 1.

Definition of a Data Dashboard. Which of the following is true with regard to a data dashboard? LO 1 i. It is a data visualization tool that gives multiple outputs and may update in real time. ii. Its outputs are often a set of KPIs for the company or some unit of the company that are aligned with organizational goals. iii. It can help an organization better understand and use its data. iv. All of the above are true with regard to a data dashboard.

Solution: iv

2. Understanding the Objectives of Effective Data Dashboards. Ideally, a data dashboard for an organization should do which of the following? LO 2 i. Present all KPIs to provide the broadest information possible. ii. Present unrelated KPIs to provide the most contrasting information possible. iii. Present both unrelated and related KPIs to provide the broadest information possible. iv. Present KPIs related to some aspect of the organization’s operations to provide information relevant to a specific problem or concern.

Solution: iv 3. Understanding Principles of Effective Data Dashboards. Which of the following is true when designing a data dashboard? LO 2 i. One does not need to be concerned with adhering to the principles of effective data visualization for the dashboard or any of its components (charts, tables, etc.). ii. One should adhere to the principles of effective data visualization for all components (charts, tables, etc.) of the dashboard but not necessarily for the overall dashboard.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

iii. One should adhere to the principles of effective data visualization for the overall dashboard but not for any of the components (charts, tables, etc.) of the dashboard but not necessarily for the overall dashboard. iv. One should adhere to the principles of effective data visualization for the dashboard and each of its components (charts, tables, etc.).

Solution: iv 4. Common Areas of Application for Data Dashboards. Which type of dashboard is used to monitor performance of an organization’s workforce by individual, division or department, or shift? LO 3 i. Technical support ii. Marketing iii. Human resource iv. Investment Solution: iii.

5. Common Areas of Application for Data Dashboards. Which type of dashboard is used to monitor contributor activity and potential for nonprofit organizations by contributor, prospective contributor, or project/campaign? LO 3 i. Technical support ii. Donor iii. Marketing iv. Manufacturing Solution: ii 6. Data Dashboard Taxonomies. Which type of dashboard might provide information on a user’s pulse, blood pressure, weight, body-mass index, and calories consumed in a day? LO 4 i. Technical support ii. Manufacturing iii. Investment analytics iv. Personal fitness Solution: iv 7. Data Dashboard Taxonomies. Which of the following most accurately describes a dynamic dashboard? LO 4 i. It regularly receives and incorporates new and revised data and incorporates these data into the dashboard. ii. It provides information in a lively manner. iii. It incorporates animation. iv. It is most useful when the organization’s KPIs change slowly.

Solution: i

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

8. Characteristics of an Interactive Data Dashboard. Which of the following most accurately describes an interactive dashboard? LO 4 i. It regularly receives and incorporates new and revised data and incorporates these data into the dashboard. ii. It allows a user to permanently alter the data displayed on the dashboard. iii. It allows a user to filter the data displayed to her or him on the dashboard. iv. It incorporates audio responses to the user.

Solution: iii 9. Restricting User Interaction in a Data Dashboard. Which of the following features allow the user to restrict the data displayed to a specific segment of users by systematically selecting values of several categories or values of variables in a nested manner? LO 4 i. Hierarchical filtering ii. Data cleansing iii. Information sifting iv. Methodical selection Solution: i 10. Data Dashboard Taxonomies. Identify which type of data dashboard is best described by each of the following descriptions. LO 4 a. Dashboards typically used by executives to monitor the status of KPIs relevant overarching organizational objectives. i. Operational ii. Tactical iii. Strategic iv. Analytic b. Dashboards typically used by analysts to identify and investigate trends, predict outcomes, and discover insights in large volumes of data. i. Operational ii. Tactical iii. Strategic iv. Analytic c. Dashboards typically used by mid-level managers to identify and assess the organization’s strengths and weaknesses in support of the development of organizational strategies. i. Operational ii. Tactical iii. Strategic iv. Analytic d. Dashboards typically used by lower level managers to monitor rapidly changing critical business conditions. i. Operational ii. Tactical iii. Strategic iv. Analytic

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

Solution: a. iii b. iv c. ii d. i 11. Overcrowding and Unnecessary Complexity in a Data Dashboard. Which of the following is not a valid strategy for avoiding overcrowding and unnecessary complexity in data dashboard design? LO 5 i. Using as many different colors as possible on the charts and tables used in the dashboard ii. Using interactive dashboard tools (drilling down, hierarchical filtering, time interval widget, customization tools) iii. Organizing the information into subsets that each address a different need of the end users and displaying information in these subsets across multiple pages iv. Avoiding inclusion of information that will not be useful to the end users Solution: i 12. Providing Effective Context in a Data Dashboard. Which of the following is an effective way to provide context for the information provided by the data dashboard? LO 5 i. Comparing the value of a KPI to an organizational goal ii. Showing how a KPI varies over time iii. Comparing the value of a KPI across customers iv. Each of the above is an effective way to provide context for the information provided by the data dashboard.

Solution: iv 13. The Data Dashboard Testing Process. Which of the following is not an important part of the process of testing a data dashboard throughout its development? LO 5 i. Reviewing progress with the management team that authorized the development of the data dashboard at critical junctures to ensure the dashboard under production is meeting the management team’s objectives ii. Allowing the general public to use and comment on the data dashboard at various stages of development to ensure the dashboard can be used by anyone iii. Allowing the ultimate users to test and comment on the data dashboard at various stages of development to ensure the dashboard is user friendly, functions in the manner expected by the users, and produces the outputs expected and needed by its users iv. Testing of the dashboard at each step by the dashboard design team to ensure the dashboard functions as the team intends Solution: ii.

14. Excel Tools for Filtering Data in a Data Dashboards. Which of the following is an Excel tool that allows the dashboard user to filter the data to be displayed in PivotTables and PivotCharts? LO 6 i. Screener ii. Dicer iii. Slicer iv. Strainer

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

Solution: iii.

15. Excel Tables and Building Data Dashboards. What is the advantage of creating an Excel Table from the raw data in Excel? LO 6 i. You can add a new record to the existing data by entering the record into the row adjacent to the last row of the table. ii. You can add a new field to the existing data by entering the field into the column adjacent to the last column of the table. iii. You can give the table a name and refer to the table by that name instead of its range of cells. iv. Each of the above is an advantage of creating a table from the raw data in Excel.

Solution: iv 16. Common Mistakes in Data Dashboard Design. Which of the following is a common mistake in designing and developing a data dashboard? LO 7 i. Using copious amounts of animation to engage and entertain the user ii. Using a different type of chart for each display in a data dashboard to provide the user with visual variety iii. Not giving careful consideration to the environment(s) in which the data dashboard will be used iv. Randomly providing unrelated but interesting trivia about the organization at the bottom of the data dashboard to encourage the user to return often Solution: iii APPLICATIONS 17. Evaluating the Design of a Data Dashboard. An alternative version of the Espléndido Jugo y Batido data dashboard shown in Figure 8.12 follows. How would you modify this alternative to improve the dashboard? LO 2

Solution: The background color is extremely bright, which makes the data dashboard difficult to read and visually unappealing. A cooler background color would be more effective.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

The contrast between the data dashboard title and background is insufficient; the title is almost impossible to read. The issue could also be corrected by changing the chart background color.

Colors on the various charts are not used consistently. On the chart of Total Sales (Thousand $) by Year Ordered, Flavor, and Category, purple represents juices, but green represents juices on the chart of Total Sales (Thousand $) by Year Ordered, Month Ordered, and Category. Green also represents 2020 on the chart of Average Time to Delivery by Distribution Center and Year Ordered. This may confuse the audience.

On the chart of Total Sales (Thousand $) by Year Ordered, Month Ordered, and Category, green represents juices and red represents smoothies. This could make this chart difficult to read for colorblind members of the audience.

All numbers provided in the table are given to two decimal places. Given the way users are likely to use these values, this may be more precision than is necessary. The numbers could possibly be rounded to integer values without loss of information, which would increase the data to ink ratio.

There is not much horizontal space between the pivot charts, pivot tables, and slicers.

This ineffective use of space gives the data dashboard a somewhat cramped appearance.

18. Evaluating the Choice of Charts in a Data Dashboard. An alternative version of the Espléndido Jugo y Batido data dashboard shown in Figure 8.12 follows. How would you modify this alternative to improve the dashboard? LO 2

Solution: The Total Sales (Thousand $) by Year Ordered, Flavor, and Category 3D pie chart uses the preattentive attributes of shape and color. However, the use of shape is ineffective because it is difficult to compare the relative sizes of the slices of the pie to determine which managers are handling the greatest number of customer accounts. The use of a different color for each slice of the pie in the chart is also overwhelming and ineffective.

Furthermore, the third dimension in this 3D pie chart does not convey any meaningful information, so it only adds clutter and reduces the data to ink ratio. The pie chart also requires considerable eye travel because the audience must match the name of each candidate with the appropriate color in the pie. Finally, there are far too many categories for this chart to be meaningful.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

The Total Sales (Thousand $) by Year Ordered, Month Ordered, and Category clustered column chart requires a great deal of eye travel to follow sales of each category across time.

The horizontal axis for the Total Sales (Thousand $) by Distribution Center, Year Ordered, and New Customer line chart represents a categorical variable (distribution center). This creates an inappropriate and potentially misleading use of the preattentive attribute of connectedness.

The ordering of the distribution centers on the Average Time to Delivery by Distribution Center and Year Ordered radar chart has an impact on how a user might interpret it. The proximity of Idaho and North Dakota makes the average time to deliver appear longer in 2018 than in 2019. However, if we exchanged the positions of North Dakota and Nebraska, the difference between 2018 and 2019 in average time to deliver would not appear as extreme. A clustered bar chart or clustered column chart would be easier for the user to understand.

There is not much horizontal space between the PivotCharts, PivotTables, and slicers. This ineffective use of space gives the data dashboard a somewhat cramped appearance.

19. Adding a Chart to a Data Dashboard. In addition to the information provided on the data dashboard shown in Figure 8.12, Espléndido Jugo y Batido management has decided it would like to include a series of charts that show the relationship between average service satisfaction rating and average product satisfaction rating across the distribution centers for each of the past three years. EJB Management would also like to include a table that provides average service satisfaction rating and average product satisfaction rating by distribution center across years. LO 2 a. What type of chart(s) would you recommend to show the relationship between the average of the service satisfaction rating and the average of product satisfaction rating across the distribution centers for each of the past three years? Explain why you would suggest such chart(s). b. How would you revise the data dashboard in Figure 8.12 to incorporate the chart or charts you suggested in part a?

Solution: a. The best chart for showing the relationship between two quantitative variables is a scatter plot. We could create a separate scatter plot with Average Service Satisfaction Rating on one axis and Average Product Satisfaction Rating on the other axis for each of past three years. Each observation (or point on a scatter plot) on these plots would coincide with one of the distribution centers. b. The current dashboard deals primarily with sales and also includes a solitary chart on delivery performance. Users who are interested in sales KPIs may not be interested in information on Service Satisfaction Rating and Product Satisfaction Rating. The information on Service Satisfaction Rating and Product Satisfaction Rating could be put on a second data dashboard (a separate tab in Excel). Because users who are interested in Service Satisfaction Rating would likely also be interested in delivery performance, the chart, slicers, and portion of the pivot table devoted to delivery performance in the current data dashboard (on Figure 8.12) could also be moved to this new page to improve the efficiency of both pages.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

20. Building a Technical Support Data Dashboard. Bogdan’s Express, a chain of sporting goods stores in Washington, wants to construct a technical support data dashboard to monitor how effectively its technical support group deals with IT problems. Management is primarily interested in the time it takes the IT support group to respond once a problem has been reported (response time) and how long it takes the group to resolve the issue after the initial response by the IT support group (time to resolution) over the most recent four months. They would like to be able to review the IT group’s performance by date, type of technical problem (email, hardware, or Internet), and office (Bellingham, Olympia, Seattle, or Spokane).

Each reported problem is immediately logged and issued a case number, and the data collected by Bogdan from its relational database includes the case number, date, office, type of technical problem, response time (in minutes), and time to resolution (in minutes).

They have also created a new field for the month during which the problem was reported.

Note that both Response Time and Time to Resolution only include time that elapses during normal business hours.

Bogdan’s staff has already created the following components for the data dashboard in Excel. LO 6 • • • •

A line chart of average response time across months by office (in the Chart1 worksheet) A line chart of average time to resolution across months by office (in the Chart2 worksheet) A clustered bar chart of average time to resolution across offices by type of technical problem (in the Chart3 worksheet) A stacked cluster column chart of number of problems reported across office by type of technical problem (in the Chart4 worksheet)

The data and these charts are available in the file bogdan_chart, and the name of the worksheet in which each chart can be found is given with the descriptions of the charts Bogdan has developed. a. Create the following slicers for the charts created by Bogdan.

• A slicer for month and a slicer for office for the chart in the Chart1 worksheet • A slicer for month and a slicer for office for the chart in the Chart2 worksheet • A slicer for office and a slicer for type of technical problem for the chart in the Chart3 worksheet • A slicer for office and a slicer for type of technical problem for the chart in the Chart4 worksheet b. Create the data dashboard by creating a new worksheet and naming it Dashboard; moving the charts and slicers from the Chart1, Chart2, Chart3, and Chart4 worksheets to the Dashboard worksheet; repositioning these charts and slicers on the Dashboard worksheet; and adding a title to the dashboard and doing whatever formatting and editing is necessary to make the dashboard functional and visually appealing. c. Amend the data dashboard you created in part b in the following ways.

• Create a single slicer to filter month for the charts created in the Chart1 and Chart2 worksheets • Create a single slicer to filter office for the charts created in the Chart1, Chart2, Chart3, and Chart4 worksheets • Create a slicer to filter type of technical problem for the charts created in the Chart3 and Chart4 worksheets

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

Once you have amended the data dashboard, rearrange the charts and slicers to create an effective and visually appealing dashboard. Test each slicer to ensure it works on the appropriate charts. d. Protect the data dashboard in part c from being revised by users. Ensure that the slicers cannot be resized or moved, password protect the Dashboard worksheet (use the password Problem820), and hide all worksheets except the Dashboard worksheet. e. The following seven entries for April 29–30 in the following table were not logged. Add these data to the BogdanData table and refresh all PivotTables and PivotCharts.

Comment on differences between the resulting dashboard and the dashboard from part d.

Case Number 1990 1994 2000 2005 2011 2012 2019

Date 29-Apr 29-Apr 29-Apr 29-Apr 30-Apr 30-Apr 30-Apr

Month Apr Apr Apr Apr Apr Apr Apr

Office Olympia Spokane Bellingham Bellingham Olympia Spokane Spokane

Type of Technical Problem hardware hardware hardware internet hardware hardware email

Response Time (Minutes) 59.9 15.8 26.7 41.4 96.1 125.6 4.5

Time to Resolution (Minutes) 23.1 64.1 53.4 12.8 14.6 55.0 45.9

Solution: a. An example of the charts and their respective slicers can be found in problem8.20(a).xlsx. The resulting data dashboard from the Chart1, Chart2, Chart3, and Chart4 worksheets should look something like the following charts:

Chart1 Worksheet

Chart2 Worksheet

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

Chart3 Worksheet

Chart4 Worksheet

b. An example of the data dashboard can be found in problem8.20(b).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Note that the charts dealing with the response time and time to resolution by office are grouped at the top of the data dashboard, the charts dealing with time to resolution are grouped on the right side of the data dashboard, and the charts that show the data by type of technical problem are grouped at the bottom of the data dashboard. Several other positions will accomplish these objectives and reduce necessary eye travel for the users.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

c. An example of the revised data dashboard can be found in problem8.20(c).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Here it is important to check each slicer to ensure it works as directed by the problem. d. Be sure to: • Set the pivot charts so they don’t move or size with cells.

• Set the slicers so they don’t move or size with cells.

• Prevent users from editing any range of cells in the Dashboard worksheet.

• Establish password protection.

• Hide all worksheets other than the Dashboard worksheet.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

e. An example of the revised BogdanData table data dashboard can be found in problem8.20(e).xlsx. The resulting data dashboard should look something like the dashboard that follows:

The addition of these seven new records does not result in any perceptible changes to the Bogdan data dashboard. This is likely because the new data are a small proportion of the total Bogdan data.

Note also that you have to reverse the steps in part c in order to add these records and refresh the pivot tables and pivot charts on this dashboard.

21. Building a Donor Data Dashboard. The American Retriever Foundation (ARF) is a not-forprofit organization dedicated to health issues faced by the six distinct retriever dog breeds (Chesapeake Bay, curly-coated, flat-coated, golden, Labrador, and Nova Scotia duck tolling). ARF needs to develop a data dashboard to monitor its donor activity and its interactions with potential donors. Management is concerned primarily with the number and dollar value of donations, the number of legacy donors (those who have donated in the past twelve months) and new potential donors solicited, and the number of solicitations that result in donations. They want to compare these results across ARF’s four development officers (Randall Shalley, Donna Sanchez, Marie Lydon, and Hoa Nguyen) by date and mode of contact (telephone, email, or personal meeting).

ARF has collected data for each solicitation initiated last year from its relational database.

These data include the solicitation number, development officer, date of solicitation, mode of solicitation, whether the solicitation resulted in a donation, and whether the solicited potential donor was a legacy donor. ARF also added a field for month in which the solicitation was made.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

ARF’s staff has already created the following components for the data dashboard in Excel.

• A stacked bar chart of the number of solicitations across development officer by whether the solicitation resulted in a donation (in the Chart1 worksheet) • A stacked bar chart of the percentage of successful solicitations across mode of solicitation by whether the solicitation resulted in a donation (in the Chart2 worksheet) • A stacked bar chart of total donations (in $1,000s) across development officer by legacy designation (in the Chart3 worksheet) • A cluster bar chart of total donations (in $1,000s) across mode of solicitation by legacy designation (in the Chart4 worksheet) The data and these charts are available in the file arf_chart, and the name of the worksheet in which each chart can be found is given with the descriptions of the charts ARF has developed. LO 6 a. Create the following for the charts created by ARF. • A slicer for development officer, a slicer for whether the solicitation resulted in a donation, and a slicer for month of solicitation for the chart in the Chart1 worksheet • A slicer for mode of solicitation, a slicer for whether the solicitation resulted in a donation, and a slicer for development officer for the chart in the Chart2 worksheet • A slicer for development officer, a slicer for legacy status of the donor, and a slicer for month of solicitation for the chart in the Chart3 worksheet • A slicer for mode of solicitation, legacy status, and month of donation for the chart in the Chart4 worksheet b. Create a data dashboard by creating a new worksheet and naming it Dashboard; moving the charts and slicers from the Chart1, Chart2, Chart3, and Chart4 worksheets to the Dashboard worksheet; repositioning the charts and slicers on the Dashboard worksheet; and adding a title to the dashboard and doing whatever formatting and editing is necessary to make the dashboard functional and visually appealing. c. Amend the data dashboard you created in part b in the following ways.

• Create a single slicer to filter month for the charts created in the Chart1, Chart2, and Chart4 worksheets • Create a single slicer to filter development officer for the charts created in the Chart1, Chart2, and Chart3 worksheets • Create a single slicer to filter whether or not a solicitation resulted in a donation for the charts created in the Chart1 and Chart2 worksheets • Create a single slicer to filter legacy status for the charts created in the Chart3 and Chart4 worksheets • Create a single slicer to filter mode of solicitation for the charts created in the Chart2 and Chart4 worksheets Once you have amended the data dashboard, rearrange the charts and slicers to create an effective and visually appealing dashboard. Test each slicer to ensure it works on the appropriate charts. d. Protect the data dashboard in part c from being revised by users. Ensure that the slicers cannot be resized or moved, password protect the Dashboard worksheet (use the password Problem821), and hide all worksheets except the Dashboard worksheet.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

e. The file arfnewdata contains 15 entries for the past year that were not originally entered into the relational data base before the data for this dashboard was retrieved.

Add these data to the arfdata table and refresh all pivot tables and pivot charts.

Comment on differences between the resulting dashboard and the dashboard from part d.

Solution: a. An example of the charts and their respective slicers can be found in problem8.21(a).xlsx. The results from the four worksheets should look something like the charts that follow:

Chart1 Worksheet

Chart2 Worksheet

Chart3 Worksheet

Chart4 Worksheet

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

b. An example of the data dashboard can be found in problem8.21(b).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Note that the charts dealing with solicitations are grouped on the left side of the data dashboard, the charts dealing with donations are grouped on the right side of the data dashboard, the charts that provide the data by development officer are grouped at the top of the data dashboard, and the charts that provide the data by mode of solicitation are grouped at the bottom of the data dashboard. Several other positions will accomplish these objectives and reduce necessary eye travel for the users.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

c. An example of the revised data dashboard can be found in problem8.21(c).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Here it is important to check each slicer to ensure it works as directed by the problem. d. Be sure to: • Set the pivot charts so they don’t move or size with cells • Set the slicers so they don’t move or size with cells • Prevent users from editing any range of cells in the Dashboard worksheet • Establish password protection • Hide all worksheets other than the Dashboard worksheet

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

e. An example of the revised arfdata table and data dashboard can be found in problem8.21(e).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Lydon’s number of solicitations and total donations increased slightly relative to the other development officers. Otherwise, there is little difference in the two data dashboards. This is likely because the new data are a small proportion of the total ARF data.

Note also that you have to reverse the steps in part c in order to add these records and refresh the pivot tables and pivot charts on this dashboard.

22. Building a Personal Fitness Data Dashboard. Late last year, Veronica Camp learned she is pre-diabetic. Her physician recommended that she immediately begin exercising regularly and limiting her calorie intact to approximately 1,500 calories per day. Her physician also advised her to monitor her systolic and diastolic blood pressure, heart rate, and blood glucose daily.

On January 1, Veronica began exercising three times a week for approximately 30 minutes, and she started monitoring her calorie intake at meals with an app she downloaded. She also started monitoring her systolic and diastolic blood pressure, heart rate, and blood glucose daily. She has created a database with these data recorded on a daily basis through November, and she has generated the following charts. LO 6 • A line chart of monthly average systolic blood pressure (in the Chart1 worksheet) • A line chart of monthly average diastolic blood pressure (in the Chart2 worksheet) • A line chart of monthly average heart rate (in the Chart3 worksheet) • A line chart of monthly average blood glucose level (in the Chart4 worksheet) • A line chart of monthly total minutes of exercise (in the Chart5 worksheet) • A line chart of average daily calorie intake for each meal across months (in the Chart6 worksheet)

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

a. Create a data dashboard for Veronica by creating a new worksheet and naming it Dashboard; moving the charts from the Chart1, Chart2, Chart3, Chart4, Chart5, and Chart6 worksheets to the Dashboard worksheet; and repositioning the charts on the Dashboard worksheet, adding a title to the dashboard, and doing whatever formatting and editing is necessary to make the dashboard functional and visually appealing. b. Create a single slicer in the data dashboard you created in part a that filters day of the week for all charts on the dashboard. Once you have amended the data dashboard, rearrange the charts and slicers to create an effective and visually appealing dashboard. Test the slicer to ensure it works on the appropriate charts. c. Create the new field Total Calories in column L of the VeronicaData Excel Table by summing Breakfast Calories, Lunch Calories, Dinner Calories, and Dessert Calories for each day. Refresh all PivotTables and PivotCharts, then add average daily total calories to the line chart of average daily calorie intake for each meal across months. Comment on differences between the resulting dashboard and the dashboard from part b. d. Protect the data dashboard in part c from being revised by users. Ensure that the slicer cannot be resized or moved, password protect the Dashboard worksheet (use the password Problem822), and hide all worksheets except the Dashboard worksheet.

Solution: a. An example of the dashboard can be found in problem8.22(a).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Note that the charts dealing with blood pressure are grouped on the left side of the data dashboard, and the charts dealing with calories (intake and burned) are grouped on the lower right side of the data dashboard. Several other positions will accomplish these objectives and reduce necessary eye travel for the users.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

b. An example of the revised dashboard can be found in problem8.22(b).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Here it is important to check the slicer to ensure it works as directed by the problem. c. An example of the revised VeronicaData table and dashboard can be found in problem8.22(c).xlsx. The resulting data dashboard should look something like the dashboard that follows:

We now see the trend in the monthly average of Veronica’s daily total calorie intake, which is useful. However, in adding this variable (which is two to three times larger than the other variables on this chart) we had to expand the range of the vertical axis

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

substantially. This effectively compressed the lines representing Veronica’s breakfast, lunch, and dinner calorie intakes. We have lost a great deal of information about the variation in her breakfast, lunch, and dinner calorie intakes; if this information is important to Veronica, we should consider creating a separate graph to display the monthly averages of total daily calorie intake. d. Be sure to: • Set the pivot charts so they don’t move or size with cells • Set the slicer so it doesn’t move or size with cells • Prevent users from editing any range of cells in the Dashboard worksheet • Establish password protection • Hide all worksheets other than the Dashboard worksheet 23. Building a Baseball Statistics Data Dashboard. The Springfield Spiders, a baseball team in the All American Baseball Association, wants to create a data dashboard for its fans.

Spiders management would like the fans to be able to review the runs scored and allowed by game, and review the number of wins and losses and the average per game attendance by opponent and by day of the week. They would also like for the fans to be able to filter each of these displays by home and away games.

The Spiders have collected data on the date, opponent, whether the game was played at home or away, how many runs the Spiders scored, how many runs the Spiders allowed their opponent to score, whether the Spiders won or lost, and the attendance for each game of the previous season. They also added a field for the day of the week, and have created the following charts for inclusion in its data dashboard. LO 6 • A line chart of runs scored and runs allowed by game (in the Chart1 worksheet) • A clustered column chart of number of wins and losses by month (in the Chart2 worksheet) • A clustered bar chart of average per game attendance across months for home and away games (in the Chart3 worksheet) • A clustered bar chart of average per game attendance across days of the week for home and away games (in the Chart4 worksheet) a. Create a data dashboard for the Spiders by creating a new worksheet and naming it Dashboard; moving the charts from the Chart1, Chart2, Chart3, and Chart4 worksheets to the Dashboard worksheet; and repositioning the charts on the Dashboard worksheet, adding a title to the dashboard, and doing whatever formatting and editing is necessary to make the dashboard functional and visually appealing. b. Amend the data dashboard you created in part b in the following ways.

• Create a slicer to filter day of the week for the charts created in the Chart1, Chart2, Chart3, and Chart4 worksheets • Create a slicer to filter opponent for the charts created in the Chart1, Chart2, Chart3, and Chart4 worksheets • Create a slicer to filter month for the charts created in the Chart1, Chart2, Chart3, and Chart4 worksheets • Create a slicer to filter home and away games for the charts created in the Chart1, Chart2, Chart3, and Chart4 worksheets Once you have amended the data dashboard, rearrange the charts and slicers to create an effective and visually appealing dashboard. Test each slicer to ensure it works on the appropriate charts.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

c. Create an alternative display of the Runs Scored and Runs Allowed by game through the following steps.

Step 1.

Create the new field Run Differential in Column I of the spidersdata table by subtracting Runs Allowed from Runs Scored for each game Refresh all PivotTables and PivotCharts

Step 2.

Create a new worksheet and rename the worksheet Chart1A Create a new pivot table and pivot chart in the Chart1A worksheet Drag the Date field to the Rows area and the Run Differential field to the Values area in the PivotFields Table pane to create a column chart Right click the horizontal axis and click Format Axis... to open the Format Axis pane, click the Axis Options button and click Labels, then select Low from the Label Position dropdown menu to position the horizontal axis at the bottom of the chart While still in the Format Axis task pane, click the Axis Options button and click Fill & Line, then in the Line area change the color of the axis to black and increase its width to 2 pt Click any bar in the chart and click Format Data Series, click the Fill & Line button, and in the Fill area click the Invert if Negative box and select the colors to be applied to the positive and negative bars

Step 3.

Replace the line chart on the dashboard that was originally created in the Chart1 worksheet with the chart you created in the Chart1A worksheet

Comment on differences between the resulting dashboard and the dashboard from part b. d. Protect the data dashboard in part c from being revised by users. Ensure that the slicers cannot be resized or moved, password protect the Dashboard worksheet (use the password Problem823), and hide all worksheets except the Dashboard worksheet. e. Data for the first month of the new season is available in the file spidersnewdata. Add this new data to the spidersdata table and delete the data for the previous season in the spidersdata table in the Data worksheet of the dashboard from part c so that the dashboard displays only the new season data. What does the resulting data dashboard communicate? What alternative approach to incorporating the new data into the existing data dashboard would you suggest?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

Solution: a. An example of the dashboard can be found in problem8.23(a).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Note that the chart dealing with runs scored and runs allowed by game is stretched across the entire top of the data dashboard. This is because the horizontal axis includes 120 unique dates, and increasing the width of the chart enables the user to more easily understand the information on the chart. The two charts dealing with per game attendance are also grouped on the lower right side of the data dashboard. b. An example of the revised dashboard can be found in problem8.23(b).xlsx. The resulting data dashboard should look something like the dashboard that follows:

Here it is important to check each slicer to ensure it works as directed by the problem.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

c. An example of the revised spidersdata table and dashboard can be found in problem8.23(c).xlsx. The resulting data dashboard should look something like the dashboard that follows:

It is now easier to identify which games the Spiders won and which games the team lost. It is also easier to discern the magnitude of the run differential for each game and the winning and losing streaks the Spiders experienced during the season.

Although line charts are generally preferred when plotting data over time on the horizontal axis, in this instance the column chart communicates more effectively. d. Be sure to: • Set the pivot charts so they don’t move or size with cells • Set the slicers so they don’t move or size with cells • Prevent users from editing any range of cells in the Dashboard worksheet • Establish password protection • Hide all worksheets other than the Dashboard worksheet

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 8: Data Dashboards

e. An example of the revised spidersdata table and dashboard can be found in problem8.23(e).xlsx. The resulting data dashboard should look something like the dashboard that follows:

We now see only results for the first month of the new season on the dashboard, and we can continue to add data as the season progresses. Note that we could have also created a field for season and retained the data for the previous season in the spidersdata table, then added a slicer to filter season for all charts on the data dashboard. This would enable the user to review data from various individual seasons.

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Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357929766; CHAPTER 9: TELLING THE TRUTH WITH DATA VISUALIZATION

TABLE OF CONTENTS End of Section Problem Solutions ......................................................................................1 CONCEPTUAL ............................................................................................................................. 1 APPLICATIONS........................................................................................................................... 9

END OF SECTION PROBLEM SOLUTIONS CONCEPTUAL 1.

Identifying Missing Data Which of the following Excel methods can be used to help identify missing data? LO 1 i. Conditional formatting to highlight missing data values. ii. Using the COUNTIF() function to find the number of missing data values. iii. Sorting the data to find missing data values. iv. All of the above.

Solution: iv.

2. Data Errors. Which of the following is true regarding data errors? LO 1 i. A data error is always identified by a unique numerical value such as 9999999. ii. Any data that are determined to be outliers should be considered data errors and should be removed. iii. Identifying outliers in a data set can be helpful in uncovering data errors. iv. Data errors occur only when data are collected manually.

Solution: iii.

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3. Types of Data Bias. Match each of the following type of data bias with the correct description. LO 2, 3 Type of Data Bias Selection bias Simpson’s paradox Survivor bias

Description Occurs when subsets of data show a specific trend, but that trend disappears, or reverses, when the data are aggregated.

Occurs when a data set is made up of a disproportionately high number of observations corresponding to positive outcomes from a particular event.

Occurs when data are drawn from a sample that had not been properly randomized to represent the intended population.

Solution: Type of Data Bias Selection bias

Simpson’s paradox

Survivor bias

Description Occurs when subsets of data show a specific trend, but that trend disappears, or reverses, when the data are aggregated.

Occurs when a data set is made up of a disproportionately high number of positive outcomes from a particular event.

Occurs when data are drawn from a sample that had not been properly randomized to represent the intended population.

4. Potential Bias in Weight-Loss Study. A clinical trial has been conducted to evaluate the efficacy of a new drug to enable weight loss for obese patients. A pool of 249 obese individuals are chosen for the study. Each study participant must track their weight at home daily to compute their body-mass index (BMI) and have a clinical evaluation once per week at a local hospital over six months to complete the clinical trial. At the end of six months, it is found that 47% of those who received the new drug completed the clinical trial. Those who completed the clinical trial are found to have reduced their BMI by 3.2 kg/m2, on average, over six months. Explain how these results could be affected by bias and how that could affect the data. LO 2 Solution: This is an example of potential survivor bias. The results of the clinical trial only apply to those that completed the six-month trial. We do not know the results of those that dropped out of the trial prior to six months. It is possible that those who were losing more weight were more likely to complete the trial, so this could bias the data to show greater weight-loss by those taking the new drug than is accurate.

5. Simpson’s Paradox in Baseball. In the sport of baseball, batting average is calculated by dividing the number of hits a player achieves by the number of official at bats. The following table shows the batting performance for Mike Legg and Edison Vasquez over two consecutive seasons. LO 3 Player Mike Legg Edison Vasquez

Season 1 Hits At Bats 14 56 112 418

Season 2 Hits At Bats 192 589 57 149

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a. Calculate the batting average for Mike Legg and Edison Vasquez in Season 1. Which player has a higher batting average in Season 1? b. Calculate the batting average for Mike Legg and Edison Vasquez in Season 2. Which player has a higher batting average in Season 2? c. Calculate the batting average for Mike Legg and Edison Vasquez over the combined Seasons 1 and 2. Which player has the higher batting average over Seasons 1 and 2? d. Explain how the results in parts a through c illustrate Simpson’s paradox.

Solution: a. Mike Legg batting average in Season 1 = 14 / 56 = 0.250 Edison Vasquez batting average in Season 1 = 112 / 418 = 0.268 So, Edison Vasquez has the higher batting average in Season 1. b. Mike Legg batting average in Season 2 = 192 / 589 = 0.326 Edison Vasquez batting average in Season 2 = 57 / 149 = 0.382 So, Edison Vasquez has the higher batting average in Season 2. c. Mike Legg batting average over Seasons 1 and 2 = (14 + 192) / (56+589) = 0.319 Edison Vasquez batting average over Seasons 1 and 2 = (112 + 57) / (418 + 149) = 0.298 So, Mike Legg has the higher batting average over Seasons 1 and 2. d. The results in parts a through c illustrate Simpson’s paradox because the subsets of data by individual season show one result (Edison Vasquez has the higher batting average in each of Season 1 and Season 2), but when the data are aggregated over the two seasons, the result is reversed (Mike Legg has the higher batting average over Seasons 1 and 2 combined).

6. Average Nominal Hourly Earnings. An economist is examining wage growth in the United States. She has collected data on average nominal hourly earnings for workers in the United States between 2006 and 2020, which are shown in the following chart. Her conclusion is that hourly earnings for workers in the United States have been steadily growing since 2006. How might this conclusion be incorrect, and how can she modify these data to investigate the appropriateness of this conclusion? LO 4

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

Solution: Because this chart is based on nominal data, the data have not been adjusted for inflation.

Therefore, the chart could give a misleading impression to the audience about the growth in buying power being provided by hourly earnings between 2006 and 2020. The economist could use a consumer price index value to adjust these data for inflation and create a chart using the inflation-adjusted values.

7. Meaning of Inflation. Which of the following are accurate statements regarding inflation?

(Select all that apply.) LO 4 i. Inflation refers to the tendency of prices to increase over time. ii. Inflation only occurs in economies that are experiencing destabilizing events like war or famine. iii. Prices that are not adjusted for inflation are referred to as nominal prices. iv. Failing to adjust for inflation in time series data that relates to monetary units can lead to misleading data visualizations. v. When creating a line chart for cost data over time, it does not matter if the data are adjusted for inflation or not.

Solution: i., iii., iv.

8. Political Polling Results in County Commissioner Election. Two candidates are running for county commissioner in Bell County, Texas: Lisa Adamek and Rosemary Andrews. The local newspaper has conducted a poll of likely voters to see where the candidates stand in regards to the election. The local newspaper has analyzed the results of its poll and posted the following chart to its website. LO 5

a. Why might this chart be misleading for the audience? b. How could this chart be improved to be less misleading for the audience?

Solution: a. It appears to show Rosemary Andrews with a substantial lead in the poll over Lisa Adamek because the vertical axis shows only the range of values between 46% and 54%.

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b

The vertical axis should start at 0 to better show the relative margin of the lead of Rosemary Andrews compared to Lisa Adamek. It would also be helpful to show the margin of error in the poll because it is based on a sample of likely voters.

9. COVID-19 Positivity Rates in Ohio. An epidemiologist has collected data on positivity rates for COVID-19 testing in the state of Ohio. The positivity rate is defined as the number of tests that come back positive for the COVID-19 virus divided by the total number of COVID-19 tests completed. The epidemiologist has created the following chart showing positivity rates in Ohio between April and October 2020. The audience for this chart is interested in trying to gain insights into any overall increasing or decreasing trends in the positivity rate for COVID-19 during this time period. LO 5

Source: Data from https://covidtracking.com/data/download How can this chart be improved to meet the needs of the audience?

Solution: The chart is too short and too wide. The compressed vertical axis and lengthened horizontal axis disguises any possible increasing or decreasing trends in the data. The minimum and maximum values of the vertical axis should also be changed. It is not effective to show values between 0% and 100% for the purposes of this chart. This range should be reduced so that trends are more apparent to the audience.

10. Dual-axis Charts. Which of the following statements are true of dual-axis charts? (Select all that apply.) LO 6 i. Dual-axis charts use a secondary vertical axis to represent one of the variables shown in the chart. ii. Dual-axis charts require two different horizontal axes and two different vertical axes for each variable displayed in the chart. iii. Dual-axis charts can be used to display two different types of data visualizations such as a line graph and a column graph on the same chart. iv. Dual-axis charts can be difficult for the audience to interpret because the magnitudes of the representation of the data cannot be compared directly without adjusting for the scale of each vertical axis. v. Dual-axis charts can only be created for pie charts and column charts.

Solution: i., iii., iv.

11. Headcount and Revenue at Maximus Fashion. Maximus Fashion is a high-end clothing store in Naperville, Illinois. The store manager would like to create a data visualization that shows trends in the store’s headcount of retail associates and revenues. For the last eight quarters, the manager has collected data on the store’s headcount of retail associates (expressed in terms of full-time equivalent [FTE] employees) and the store’s revenues. The manager has chosen to display these data as the dual-axis chart that

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follows. The audience for this chart is an informal advisory group for the store who has considerable experience in fashion, but little experience with financial analysis or data visualization in general. LO 5, 6

a. What possible confusion could the use of this chart create for the audience? b. How could the store manager redesign this chart to better present these data to the audience?

Solution: a. It is difficult to see relationships between the two lines on the same chart with different vertical axes. The chart makes it appear as though revenue and headcount are nearly the same in Quarters 3 and 4. And because the vertical axis for revenue has a minimum value of $0, it is hard to see any trends in the line representing revenue in the chart. b. It would be better to display this as two different charts: one chart with only headcount and one chart with only revenue. The charts could be stacked vertically so that the horizontal axes align by quarter. Further, the vertical axis range for revenue should be changed so that any trends in these data are more apparent.

12. Investing in Amazon.com Stock. Marisha Ray is a thirty-year-old software engineer. Marisha is considering investing in a large amount of Amazon.com stock that she plans to hold until her retirement around age 60. Consider the following charts. Each chart shows the performance of Amazon.com stock, but over different time periods. One chart shows the performance of Amazon.com stock over the last five days, and the other chart shows the performance of Amazon.com stock over the last five years. Which chart would be the best chart to show to Marisha as she considers investing in Amazon.com stock for her retirement savings? Why? LO 7

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

Solution: Because Marisha plans to hold the Amazon.com stock for a long time period, the chart showing the performance of the stock over the last five days is not particularly helpful for her. The chart showing the performance of the Amazon.com stock over the last five years could be more indicative of the expected long-term performance of the stock, so this chart is preferred over the chart showing the five-day performance.

13. Communicating Insights with Time Series Charts. Which of the following properties of a time series chart can influence the insights communicated to the audience? LO 7 i. The frequency with which the data are shown. ii. The start and end date used on the horizontal axis for the chart. iii. The range of values displayed on the vertical axis. iv. All of the above.

Solution: iv.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

14. Poverty and Millionaires Choropleth Maps. The following choropleth maps show the number of people living in poverty by state and the number of millionaires by state, respectively. Interestingly, these choropleth maps appear to be very similar; states with a high level of millionaires also appear to be the same states with high levels of poverty.

One possible insight from comparing these two choropleth maps is that poverty and high wealth appear to be positively correlated. LO 8

a. Why might it be incorrect to conclude that higher rates of poverty occur in states that have higher rates of wealth based on these two choropleth maps? b. How would you improve these choropleth maps to provide a better comparison between poverty rates and rates of high wealth by state?

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Solution: a. Because both choropleth maps are using absolute values that are not adjusted for the population in each state, it is possible that these maps are simply showing states with the highest populations. This may not be the same as maps showing the highest rate of poverty and rate of wealth. b. To adjust for population, we can divide the number of people living in poverty in each state and the number of millionaires in each state by the population of the state. This would then give us better measures of the rates of poverty and wealth in each state.

APPLICATIONS 15. Java Cup Taste Data. Huron Lakes Candies (HLC) has developed a new candy bar called Java Cup that is a milk chocolate cup with a coffee-cream center. In order to assess the market potential of Java Cup, HLC has developed a taste test and follow-up survey.

Respondents were asked to taste Java Cup and then rate Java Cup’s taste, texture, creaminess of filling, sweetness, and depth of the chocolate flavor of the cup on a 100point scale. The taste test and survey were administered to 217 randomly selected adult consumers. Data collected from each respondent are provided in the file javacup. LO 1 a. Are there any missing values in HLC’s survey data? If so, identify the respondents for which data are missing and indicate which values are missing for each of these respondents. b. Are there any values in HLC’s survey data that appear to be erroneous? If so, identify the respondents for which data appear to be erroneous and indicate which values appear to be erroneous for each of these respondents.

Solution: a. Using the Excel function COUNTBLANK, we find that there is one blank response in column C (Texture) and one blank response in column F (Depth of Chocolate Flavor of the Cup). With further investigation, we find that the value of texture for respondent 157 is missing, and the value of Depth of the Chocolate Flavor of the Cup for respondent 199 is missing. b. To help us identify erroneous values, we calculate the Average, Standard Deviation, and Minimum and Maximum values for each variable. # Missing Values:

0

1

0

0

1

Average:

72.29

105.94

77.11

78.51

77.36

Standard Deviation:

20.21

447.89

19.14

66.15

17.69

Minimum:

8.40

13.00

19.00

0.67

11.00

Maximum:

100.00

6666.00

120.00

997.00

100.00

We can immediately spot some surprising values in Column C (Texture) and Column E (Sweetness). Further examination identifies the following: the value of Texture for respondent 68 is 6666, which is outside the range for this variable; the value of sweetness for respondent 72 is 997, which is outside the range for this variable; the value of Sweetness for respondent 85 is 0.67, which is outside the range for this variable and is not an integer. Additional examination of the other responses shows that the value of Taste for respondent 90 is 8.4, which is not an integer, and the value of Creaminess of Filling for respondent 197 is 120, which is outside the range for this variable.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

16. Major League Baseball Attendance. Marilyn Marshall, a professor of sports economics, has obtained a data set of home attendance for each of the 30 major league baseball franchised for each season from 2010 through 2016. Dr. Marshall suspects the data, provided in the file attendmlb, is in need of a thorough cleansing. You should also find a reliable external source of Major League Baseball attendance for each franchise between 2010 and 2016 to use to help you identify appropriate imputation values for data missing in the attendmlb file. (Hint: ESPN.com contains attendance data for Major League Baseball franchises.) a. Are there any missing values in Dr. Marshall’s data? If so, identify the teams and seasons for which data are missing and which values are missing for each of these teams and seasons. Use the reliable external source of Major League Baseball Attendance for each franchise between 2010 and 2016 to find the correct value in each instance. b. Are there any values in Dr. Marshall’s data that appear to be erroneous? If so, identify the teams and seasons for which data appear to be erroneous and indicate which values appear to be erroneous for each of these teams and seasons. Use the reliable external source of Major League Baseball attendance for each franchise between 2010 and 2016 to find the correct value in each instance.

Solution: a. Using the Excel function COUNTBLANK, we find that one observation is missing in column B and one observation missing in column C. Additional investigation shows that the missing value in column B is for year 2016 for the Phillies and the missing value in column C is for year 2016 for the Marlins. Review of major league baseball attendance data that are available from a reliable source shows that the Phillies’ attendance in 2016 was 1,915,144, which is consistent with the value of the Phillies’ attendance for the observation with the missing value of season. This supports our suspicion that the value of season for this observation is 2016. Review of major league baseball attendance data that are available from a reliable source shows that the Marlins’ 2016 attendance was 1,712,417. (Note that we use the reference ESPN.com, at http://www.espn.com/mlb/attendance as of October 24, 2020, as our reliable data source for comparison.) b. To help us identify erroneous values, we calculate the average, standard deviation, minimum and maximum values for Season and Attendance. (Note that we use the reference ESPN.com, at http://www.espn.com/mlb/attendance as of May 14, 2017, as our reliable data source for comparison.) # Missing Values:

1

1

2004

2,656,439.99

Standard Deviation:

124

2,343,432.50

Minimum:

214

-3,365,256.00

Maximum:

2016

26,426,820.00

Average:

We immediately identify that there is an erroneous value for Season as all values should be between 2014 and 2016, but the minimum value is 214. We also identify that the minimum and maximum values for Attendance appear questionable. Review of major league baseball attendance data that are available from a reliable source shows that the Cubs’ attendance in 2014 was 2,652,113, which is consistent with the value of

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the Cubs’ attendance for the observation with the missing value of season. This supports our suspicion that the value of season for this observation is 2014.

The value for attendance for the Giants in 2016 is –3,365,256, which is unrealistic.

Review of major league baseball attendance data that are available from a reliable source shows that the Giants’ 2016 attendance was 3,365,256.

The value for attendance for the Cubs in 2013 is 26,426,820, which is unusually large.

Review of major league baseball attendance data that are available from a reliable source shows that the Cubs’ 2013 attendance was 2,642,682.

We can also sort the data in Excel by Team Name to help us identify attendance values that seem outside the norm for that team. Additional analysis of individual attendance values shows the following.

The value for attendance for the Royals in 2011 is 172,445, which is unusually small.

Review of major league baseball attendance data that are available from a reliable source shows that the Royals’ 2011 attendance was 1,724,450.

The value for attendance for the Marlins in 2014 is 9,732,283, which is unusually large compared to other season attendance values for the Marlins. Review of major league baseball attendance data that are available from a reliable source shows that the Marlins’ 2014 attendance was 1,732,283.

The value for attendance for the Marlins in 2015 is 752,235, which is unusually small compared to other season attendance values for the Marlins. Review of major league baseball attendance data that are available from a reliable source shows that the Marlins’ 2015 attendance was 1,752,235.

The value for attendance for the Orioles in 2014 is 22,464,473, which is unusually large.

Review of major league baseball attendance data that are available from a reliable source shows that the Orioles’ 2014 attendance was 2,464,473.

17. Unemployment Rate and Delinquent Loans. The rate of unemployment is often correlated with the amount of delinquent loans because people have a more difficult time repaying loans on time if they are unemployed. The file unemployrate contains data on unemployment rates and percent of delinquent loans for 27 cities in the United States. LO 2 a. Create a scatter chart to examine the relationship between unemployment rate and percent of delinquent loans in these cities. Does there appear to be a relationship between unemployment rate and delinquent loans? b. Based on the scatter chart you created in part a, are there any data points that would cause concern as possibly being a data error?

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Solution: a.

There appears to be a relationship between unemployment rate and percent of delinquent loans. As the unemployment rate increases, it appears that the percent of delinquent loans also generally increases. b. The data point for Philadelphia (6.2, 14.75) could be a data error. See the following figure.

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18. Amount of Vacation Used at Consulting Firm. Guaraldi and Associates is a management consulting firm located in Manhattan. The firm is interested in examining the relationship between the amount of vacation that their consultants use per year and how long the consultant has been with the firm. All consultants at Guaraldi and Associates, other than the Managing Partners, are considered either Junior Consultants or Senior Consultants based on their skills and expertise. The file guaraldi contains data on all Junior and Senior Consultants at Guaraldi and Associates including the years of service the consultant has at the firm and the number of hours that the consultant took as vacation last year. LO 4 a. Create a scatter chart and add a trendline to examine the relationship between years of service and amount of vacation time used for all consultants at Guaraldi and Associates. Based on the scatter charts, what appears to be the relationship between years of service and amount of vacation time used? b. Create a scatter chart for the same data, but this time differentiate the points in the scatter chart based on whether the consultant is junior or senior. Do you see the same relationship in this scatter chart individually for junior and senior consultants as you saw in part a for all consultants? c. Do the results in parts a and b provide an example of Simpson’s paradox? Why or why not?

Solution: a. Based on this scatter chart and trendline there appears to be a negative relationship between Years of Service and Vacation Hours Used. Consultants with more years of service tend to take less vacation.

Examining Vacation Time Usage at Guaraldi and Associates Vacation Hours Used Last Year

100 90 80 70 60 50 40 30

20 10 0

0

2

4

6

8

10

Years of Service

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b. When we separate the data into Junior and Senior Consultants, the relationship changes. There no longer appears to be a negative relationship between years of service and amount of vacation hours used. In fact, there appears to be a slightly positive relationship for both the junior and senior consultants individually. For both groups, the amount of vacation used tends to slightly increase as years of service increases. However, Junior Consultants tend to take much less vacation than Senior Consultants regardless of their years of service.

Examining Vacation Time Usage at Guaraldi and Associates by Type of Consultant Vacation Hours Used Last Year Junior

100

Senior

90

80 70 60 50

40 30 20 10 0

0

2

4

6

8 10 Years of Service

c. Yes, because the trend that appears in the complete data set disappears when the data are split into subgroups, this is an example of Simpson’s paradox.

19. Average Nominal Hourly Earnings (Revisited). In this problem, we revisit the data used in Problem 6. The file nominalwages contains the data that were used to create the line chart shown in Problem 6. This file also contains price index data that can be used to adjust the nominal hourly earnings in the file for inflation. Use the price index data to adjust the nominal hourly earnings data for inflation using 3/1/2006 as the base period.

Create a line chart for the inflation-adjusted hourly earnings and compare it to the line chart in Problem 6. What does the inflation-adjusted hourly earnings data suggest about the growth of hourly wages between 2006 and 2020? LO 5

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

Solution:

Compared to the line chart in Problem 7, the inflation adjusted hourly earnings grow much more slowly. The inflation adjusted hourly earnings are nearly flat between 2006 and 2020.

This means that the growth in hourly earnings has barely kept up with the rate of inflation.

20. Political Polling Results in County Commissioner Election (Revisited). In this problem, we revisit the chart from Problem 8. The chart shown in Problem 8 could be misleading for an audience comparing the polling results of the candidates Lisa Adamek and Rosemary Andrews. Redesign this chart using the data in the file commissioner_chart to be a more effective data visualization for the polling results for these two candidates. LO 6 Solution:

In this revised chart, the vertical axis ranges from 0% to 60%. We have also added 95% confidence interval bands to the columns.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

21. COVID-19 Positivity Rates in Ohio (Revisited). In this problem, we revisit the chart from Problem 9. The chart in Problem 9 could mislead an audience about trends related to the positivity rate for COVID-19 tests in Ohio between April and October 2020. Use the data in the file positivityohio_chart to redesign the chart to present a more effective data visualization for an audience trying to gain insights into the positivity rate of COVID-19 testing in Ohio. LO 6 Solution:

Here we have redesigned the chart to make it taller so that the vertical axis is not as compressed as the chart shown in Problem 9. We have also changed the vertical axis scale so that the maximum value on the vertical axis is 20% instead of 100%. This makes it much easier for the audience to discern trends in positivity rates for COVID-19 in Ohio during this time period.

22. Headcount and Revenue at Maximus Fashion (Revisited). In this problem, we revisit the chart from Problem 11. The dual-axis chart used in Problem 11 is likely not an effective chart for an audience with little experience in finance and data visualization. Using the data in the file maximus_chart, redesign this dual-axis chart to be more effective for the audience. LO 7

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

Solution:

Here we have split the dual-axis chart into two different charts: one showing the quarterly revenue and one showing the number of retail associates. We align these vertically so that the audience can compare the two charts using the same horizontal axis but it is clear that each chart uses a different vertical axis.

23. Poverty and Millionaires Choropleth Maps (Revisited). In this problem, we revisit the charts from Problem 14. The choropleth maps in the following problem show the number of people living in poverty by state, and the number of millionaires by state, respectively.

The file povertymillionaires contains data on the number of people living in poverty in each state, the number of millionaires in each state and the population of each state. a. Create a choropleth map that shows the poverty rate as a percent of total state population in each state. Which states have the highest poverty rates?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

b. Create a choropleth map that shows the rate of millionaires as a percent of total state population. Which states have the highest rate of millionaires? c. Compare the choropleth maps in parts a and b with the maps in Problem 14. Do you see the same relationship in the maps in parts a and b between the poverty rate and rate of millionaires as is seen in the maps in Problem 14? Why or why not?

Solution: a.

States such as New Mexico, Mississippi, and Louisiana have the highest poverty rates in the United States. b.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357929766; Chapter 9: Telling the Truth with Data Visualization

States in the northeast of the United States such as Connecticut, New Jersey, Massachusetts, and New Hampshire as well as Alaska and Hawaii have the highest rate of millionaires as a percent of state population. c. The maps for the poverty rate and rate of millionaires as percentages of state population are quite different where the maps in Problem 14 were similar. This is because the maps in Problem 14 were not adjusted for state populations, so both maps in Problem 14 are effectively showing the states with the largest populations.

When the data are adjusted to represent percentages of state population in this problem, we see that there is little evidence of positive correlation (and considerable evidence of negative correlation) between poverty rates and rate of millionaires by state.

Note also that the variation between states is much lower for the rate of millionaires than for the poverty rate. The rate of millionaires varies between 1.53% and 3% while the poverty rate varies between 7.30% and 19.12%.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

Solution and Answer Guide

CAMM/COCHRAN/FRY/OHLMANN, DATA VISUALIZATION - EXPLORING AND EXPLAINING WITH DATA, 2ND EDITION, © 2025, 9780357631348; MULTI-CHAPTER CASES

TABLE OF CONTENTS Case Problem 1: Piedmont General Hospital......................................................................1 Case Problem 2: Bayani Bulb Bases .................................................................................. 6 Case Problem 3: International Monetary Fund Housing Affordability ...........................13 Case Problem 4: Short Term Rental Market ....................................................................17

CASE PROBLEM 1: PIEDMONT GENERAL HOSPITAL Piedmont General Hospital (PGH) is a large healthcare facility located in the southeastern United States, renowned for its commitment to quality care of its patients. Megan Avery is the Vice President of Quality for PGH. Megan manages the team responsible for implementing and overseeing all quality and risk control programs.

PGH has recently noticed an uptick in the readmission rate. A readmission is when a discharged patient returns to the hospital for the same or related care within 30 days of being discharged from the hospital. Readmissions strain resources and negatively impact patient outcomes and patient satisfaction. Furthermore, for patients on Medicare, the Hospital Readmissions Reduction Program passed by Congress financially penalizes hospitals by reducing the amount paid for services when the hospital exceeds their expected number of readmissions. PGH has, to date, never exceeded its expected number of readmissions, and Megan wants to ensure that PGH continues to have fewer readmissions than expected.

Megan has asked her team to investigate factors that lead to higher readmission rates. Megan believes that if factors that seem related to higher readmission rates can be identified from the analysis of patient records, the team will be able to create strategies to mitigate the number of readmissions. To that end, David Moore, a data analyst on Megan’s team, has collected a sample of 500 records for patients admitted for congestive heart disease. 1 The data set in the file readmissions includes the following variables: • •

1

Patient ID Number – patient identification numbers from 1 to 500 to protect the privacy of the patient Age – the age of the patient at the time of the original admission to the hospital

The data in this case are simulated.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

• • • • •

Comorbidities – health conditions other than congestive heart failure present in the patient Length of Stay – duration of the stay in the hospital in the original admission Discharge Instructions – instructions given to the patient when discharged (exercise and/or medication) Compliance – how well the patient complied with the discharge instructions (scored as low, medium, or high) Readmission status – whether or not the patient was readmitted for congestive heart failure within 30 days of discharge (1 = yes and 0 = no)

Now, David needs to analyze the data and develop a report for Megan. LO 2.1, 2.2, 2.3, 2.4, 6.3, 6.5 SUMMARY REPORT David’s goal is to develop a report that shows which factors (if any) seem to be related to patient readmission. Your job is to conduct the analysis and help David with the report. Begin by investigating each of the following relationships with an appropriate chart: 1.

2.

3.

4.

5.

How is readmission rate related to age? Consider age as a categorical variable with categories 40–49, 50–59, 60–69, and 70–80, and construct a column chart to answer this question.

How is readmission rate related to length of stay?

Is readmission rate higher for certain comorbidities?

How is readmission rate related to compliance?

Construct a clustered column chart with readmission rates for the comorbidities by age category.

Based on your analysis, what are the characteristics of patients that should be targeted first for interventions and/or special follow-up care?

Your report should include the charts and tables generated to answer the questions posed and a brief description and conclusion of each.

Solution: If we convert age from a continuous variable to categories of ranges of ages, all of the variables except length of stay can be viewed as categorical. Hence, we will rely on column charts to explore the 500 patient records. We begin by answering each posed question, and then we will provide a recommendation.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

How is readmission rate related to age? Consider age categories 40–49, 50–59, 60–69 and 70–80.

The following column chart shows that the older age categories have higher readmission rates.

How is readmission rate related to length of stay?

The following chart shows that the lowest length of stay (2 days) and the two highest lengths of stay (9 and 10 days) have the highest readmission rates.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

Is readmission rate higher for certain comorbidities?

The following chart shows that patients with hypertension or diabetes have higher readmission rates, and diabetes has the highest (32%).

How is readmission rate related to compliance?

Unsurprisingly, low compliance has the highest readmission rate (32%).

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

Construct a clustered column chart with readmission rates for the comorbidities by age category.

The numbers needed to answer this question can be calculated with a pivot table, as shown below:

From the above pivot table, we can construct the smaller readmission rate table we need. We are concerned with readmission rates. We can calculate the percentage of patients who are in the 40–49 age category with diabetes who are readmitted as 9/42 = .2143 or 21%. The percentage of patients who are in the 40–49 age category with hypertension is 9/38 = .2368 or 24%. The other results in the following table are calculated in a similar manner.

Based on this table, we can construct a clustered column chart.

As the following chart shows, older patients with diabetes have a much higher readmission rate (45%). Hence, better understanding of patients aged 70–80 years with diabetes and perhaps targeting them with new interventions and programs would be a good place to start.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

CASE PROBLEM 2: BAYANI BULB BASES Bayani Bulb Base, Inc (BBB) produces and sells Edison screw bases that are used by its wholesale customers as inputs into the production of LED (light-emitting diode) bulbs.

The six light bulb bases BBB produces are: • • • • • •

E11 - Miniature Candelabra/Sconce (11 mm) E12 - Candelabra/Sconce (12 mm) E14 - European (14 mm) E17 - Intermediate (17 mm) E26 - Standard/North American (26 mm) E39 - Mogul/High Lumen (39 mm)

BBB manufactures its light bulb bases in Appleton, Wisconsin; Greenville, South Carolina; and Henderson, Nevada. These modern factories are completely automated; all functions are performed by robots, so BBB factories are capable of production 24 hours per day and seven days per week. When BBB receives an order, it is immediately shipped from one of BBB’s warehouses to the customer, and one of BBB’s factories is immediately assigned to produce replacements and ship them to that warehouse to replenish BBB’s inventory.

The finished bases are packed in cases of 244, and BBB’s factories each have limited capacity to temporarily store cases of finished bases before they are shipped to BBB’s warehouses in Boise, Idaho; Scranton, Pennsylvania; Jackson, Mississippi; and Sante Fe, New Mexico. The limited storage capacity at the factories compels BBB’s factories to ship cases of finished bases within 2.5 days of manufacturing and packing on average. Once the cases of finished bases arrive at the warehouses, robots automatically unload and store them as directed by BBB’s inventory control system.

In addition to BBB management’s concern about the length of time cases of finished bases remain in temporary storage at each of its factories, BBB management also wants to determine whether any factory tends to produce cases of finished bases at slower or faster rates than the other two factories and whether any factory tends to ship cases of finished bases at slower or faster rates than the other two factories. Additionally, for each type of light bulb base, BBB management wants to monitor its monthly productivity by factory and the monthly number of cases of finished bases shipped from each factory to each warehouse.

Members of the BBB executive team asked Marisa Vallejo, Directory of Information Technology (IT), to develop a tool that will enable them to quickly gain insight into the status of each of these issues. Marisa decided that her staff could design a dashboard that would effectively and quickly provide these insights in a visual manner that would be easy for BBB’s management to assimilate.

Marisa’s first step was to task her staff with identifying and collecting the data necessary to support the development of this data dashboard. The IT staff collected the following data for each order placed with BBB over the past 36 months.

• • • •

Order Number Product Ordered Cases Ordered Factory in which the Order is Produced

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

• • • •

Warehouse to which the Order is Shipped Date Ordered Date Manufactured by Factory Date Shipped by Factory to Warehouse

These data are available in the file bbb. Because each row in these data represents an order of cases that has been fulfilled (produced and shipped), the field Cases Ordered also corresponds to the number of cases produced and the number of cases shipped. LO 2.1, 2.3, 2.4, 2.5, 4.3, 4.5, 8.6 SUMMARY REPORT Marisa’s objective is to develop a data dashboard that provides BBB executives with insight into the time cases of finished bases remain in temporary storage in each of its factories, the time to produce cases of finished bases in each of its factories, and the time to ship cases of finished bases from each of its factories. For each type of light bulb base, the dashboard should also enable BBB executives to determine the monthly number of cases of finished bases produced by each factory and the monthly number of cases of finished bases shipped from each factory to each warehouse.

Assist Marisa by first determining and creating the most appropriate chart of: • • • • •

Monthly average time to produce finished bases for each of its factories by product and year Monthly average time cases of finished bases remain in temporary storage in each of its factories by product and year Monthly average time to ship cases of finished bases for each of its factories by product and year Monthly number of cases of finished bases produced by each factory by product and year Monthly number of cases of finished bases shipped from each factory to each warehouse by product and year

Use these charts to build a dashboard that will enable the user to view them and select the factory, product, year, and warehouse for display. The dashboard should allow the user to control the selected factory, year, and product simultaneously.

Based on your results, your report should include discussions of the following questions: 1.

2.

3.

4.

5.

Is the monthly average time to produce finished cases of bases for any BBB product(s) by any BBB factory substantially higher or lower than the other BBB factories?

Is any BBB factory systematically storing cases of finished bases of any BBB product(s) in temporary storage in excess of BBB’s standard of an average of no more than 2.5 days?

Is the monthly average time to ship finished cases of bases for any BBB factory substantially superior or inferior to the other BBB factories for any BBB product(s)?

Is the monthly average cases of finished bases produced by any BBB factory systematically greater or less than the other BBB factories for any BBB product(s)?

Is the monthly number of cases of finished bases shipped for any factory-towarehouse combination systematically greater or less than the other combinations of BBB factories and warehouses?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

Solution: We begin by opening the file bbb in Excel and creating the following variables for each order in the Data tab.

• • •

Days to Produce (the time that passes from the Date Ordered to the Date Manufactured) Days Stored in Factory (the time that passes from the Date Manufactured to the Date Shipped) Days to Ship (the time that passes from the Date Ordered to the Date Shipped)

Next, we determine the type of charts and the slicer(s) to display: •

the average time to produce finished bases of each BBB product for each of its factories by month A line chart with Month and Year on the horizontal axis, Days to Produce on the vertical axis, Factory on the legend, and slicers for Year, Product, and Factory

•

the average amount of time cases of finished bases of each BBB product remain in temporary storage in each of its factories by month A line chart with Month and Year on the horizontal axis, Days Stored in Factory on the vertical axis, Factory on the legend, and slicers for Year, Product, and Factory

•

the average time to ship cases of finished bases of each BBB product for each of its factories by month A stacked bar chart with Month and Year on the horizontal axis, Average Days to Ship on the vertical axis, Average of Days to Produce and Average of Stored in Factory (which equals Average Days to Ship on the legend) and slicers for Product and Factory

•

the monthly productivity for each factory for each BBB product A bar chart with Month and Year on the horizontal axis, Cases Ordered on the vertical axis, Factory on the legend, and slicers for Product, Year, and Factory

•

the monthly number of cases of finished bases shipped from each factory to each warehouse A bar chart with Month and Year on the horizontal axis, Cases Ordered on the vertical axis, Factory on the legend, and slicers for Product, Year, Factory, and Warehouse

A single slicer for each of Factory, Product, and Year will control these five charts simultaneously.

After creating an Excel Table from the data in the bbb file’s Data tab and naming the Table BBBProd, we create each chart for the dashboard.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

•

A line chart with Month and Year on the horizontal axis, Days to Produce on the vertical axis, Factory on the legend, and slicers for Year, Product, and Factory

•

A line chart with Month and Year on the horizontal axis, Days Stored in Factory on the vertical axis, Factory on the legend, and slicers for Year, Product, and Factory

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

•

A stacked bar chart with Month and Year on the horizontal axis, Average Days to Ship on the vertical axis, Average of Days to Produce and Average of Days Stored in Factory (which equals Average Days to Ship) on the legend, and slicers for Product and Factory

•

A bar chart with Month and Year on the horizontal axis, Cases Produced on the vertical axis, Factory on the legend, and slicers for Product, Year, and Factory

•

A bar chart with Month and Year on the horizontal axis, Cases Shipped on the vertical axis, Factory on the legend, and slicers for Product, Year, Factory, and Warehouse

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

Next, we decide how to arrange the charts and slicers on the dashboard. We will use the following layout.

After creating a new worksheet and renaming the new worksheet Dashboard, we will complete the construction of the BBB data dashboard in this layout. The resulting BBB dashboard follows.

Now, set each slicer to control all charts in the dashboard on which they are displayed, then use settings to prevent users from altering the dashboard while still allowing them to interact with the dashboard through the slicers and filters.

We can now use the dashboard to assist Marisa with her analysis and answer BBB management’s questions.

•

Is the monthly average time to produce finished cases of bases for any BBB product(s) by any BBB factory substantially higher or lower than the other BBB factories?

Using the Factory and Product slicers together allows us to look at monthly average Days to Produce for each factory individually for each product. The monthly average time to produce the E11 and E39 products appears to be systematically higher in the Appleton, WI factory.

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11

Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

•

Is any BBB factory systematically storing cases of finished bases of any BBB product(s) in temporary storage in excess of BBB’s standard of an average of no more than 2.5 days?

Using the Factory and Product slicers together allows us to look at the monthly average Days Stored in Factory for each factory individually for each product. No BBB factory appears to have a systematically high monthly average time in storage for any of BBB’s products.

•

Is the monthly average time to ship finished cases of bases for any BBB factory substantially superior or inferior to the other BBB factories for any BBB product(s)?

Using the Factory and Product slicers together allows us to look at monthly average Days to Ship for each factory individually for each product. The monthly average time to produce the E11 and E39 products appears to be systematically higher in the Appleton, WI factory. This is not surprising because monthly average Time to Produce = monthly average Days to Produce + monthly average Days Stored in Factory for each factory individually for each product, and we have already seen that the monthly average time to produce the E11 and E39 products appears to be systematically higher in the Appleton, WI factory.

•

Is the monthly average cases of finished bases produced by any BBB factory systematically greater or less than the other BBB factories for any BBB product(s)?

Using the Factory and Product slicers together allows us to look at monthly average Cases of Finished Bases Produced for each factory individually for each product. The monthly average cases produced for the E14 and E26 products appears to be systematically higher in all three BBB factories. This is not surprising because these are the two products for which BBB produces the greatest quantity. We also note that the monthly average cases produced for the E12 product in the Henderson, NV factory appears to be systematically higher than in the other BBB factories.

•

Is the monthly number of cases of finished bases shipped for any factory-towarehouse combination systematically greater or less than the other combinations of BBB factories and warehouses?

Using the Factory and Warehouse slicers together allows us to look at the monthly average Cases of Finished Bases Shipped by each factory to each warehouse. The monthly average cases shipped appears to be systematically higher for the following combinations of BBB factories and warehouses: o o o o

Appleton, WI to Jackson, MS Greenville, SC to Jackson, MS Henderson, NV to Boise, ID Henderson, NV to Jackson, MS

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

CASE PROBLEM 3: INTERNATIONAL MONETARY FUND HOUSING AFFORDABILITY The International Monetary Fund (IMF) was formed in 1944 near the end of World War II. The IMF is headquartered in Washington, D.C., and it represents 190 member countries. The stated mission of the IMF is to work “to foster global monetary cooperation, secure financial stability, facilitate international trade, promote high employment and sustainable economic growth, and reduce poverty around the world” (see https://www.imf.org/en/About). The IMF often assists countries suffering financial crises by making loans using its resources of more than 600 billion US dollars, which are collected from member countries.

The IMF is also a leading global economic data and research organization, charged with watching over the global economy and calling attention to potential economic risks and major events. The IMF publishes many research reports, including the annual World Economic Outlook and more specialized working papers and visualizations based on world economic data and specific issues.

Gita Kotrangada is a research assistant for the IMF. Gita has been asked to compare housing affordability in the United States with Germany between the years of 1985 and 2020. Gita needs to create a single chart that best compares housing affordability for the United States and Germany over this time period. The data Gita has available to create this chart are median residential non-apartment home prices, median per capita incomes, and consumer price index values for both the United States and Germany during the years from 1985 to 2020 in the file imf. All home prices and income values are provided as nominal values (not adjusted for inflation). LO 2.1, 2.2, 2.3, 2.4, 9.4, 9.5, 9.6 SUMMARY REPORT Gita’s goal is to create a single chart that best compares housing affordability in the United States and Germany during the years from 1985 to 2020. To help understand the best way to visualize these data, perform the following analysis.

1.

2.

3.

4.

5.

Create a combo line chart displaying nominal home prices and nominal median per capita income in the United States. Create a similar combo line chart for Germany.

Create a line chart that compares the nominal home price in the United States to the nominal home price in Germany. Create a similar line chart comparing nominal incomes in the United States and Germany.

Create a nominal housing affordability metric by using the ratio of home prices to income for each country and create a line chart comparing these housing affordability metrics in the United States to Germany.

Create a chart comparing the housing affordability metrics for the United States and Germany that adjusts for inflation.

Based on the charts created in parts (1)-(4), which chart do you think presents the best comparison for these data? Why?

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

Solution: Nominal home prices and annual incomes for the United States and Germany as combo line charts are shown below. Notice that these combo charts are difficult to interpret and can be misleading. Both charts make it appear that annual income values in the United States and Germany have risen above housing cost values, but this is incorrect. Housing costs in both countries have been considerably higher than annual income values for the entire time period of our data set.

Charts comparing the nominal housing prices in the United States and Germany and nominal annual incomes in the United States and Germany are shown below. These charts show that housing prices in Germany have been consistently higher than in the United States, while annual incomes have been consistently higher in the United States than in Germany.

Therefore, we can conclude that it is likely easier to afford a house in the United States than in Germany. However, it is difficult to interpret from these graphs just how much easier it is to afford a house in the United States than in Germany. We also must realize that these values are not adjusted for inflation and that the values for the United States are given in US$ while the values for Germany are given in Euros, €.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

A chart comparing the nominal housing affordability metric (= housing cost/annual income) for the United States and Germany is shown below. This chart makes it appear that Germany’s relative housing affordability metric has decreased sharply compared to the United States’. This would mean that it is much easier to afford a house in Germany in 2020 than it was in 1985. And, while Germany’s housing affordability metric remains higher than the United States’, it is much closer to the United States’ value now than in the past.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

Finally, a chart comparing the inflation-adjusted housing affordability metric (= housing cost/annual income) for the United States and Germany is shown below. This chart is somewhat similar to the previous chart using nominal housing affordability metric values. But, when adjusted for relative inflation rates (and using the same range for the vertical axes), we notice that the inflation-adjusted change in Germany’s housing affordability metric is even more dramatic than it appeared using the nominal values. It appears that it is much easier to afford a house in Germany in 2020 than in 1985 and that the inflation-adjusted housing affordability metric in Germany is much closer to the United States in 2020 than it was in 1985.

Based on this analysis, it appears that the final chart we created that compares real housing affordability metric values adjusted for inflation is the best way to present these data.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

CASE PROBLEM 4: SHORT TERM RENTAL MARKET Unlike traditional hotels, short-term rentals typically involve renting private residences for stays ranging from a single night to a few weeks. Fostered by the emergence of platforms such as Vrbo (Vacation Rentals by Owner) and Airbnb, the short-term rental market has become a robust sector of the lodging industry. These platforms provide a centralized online marketplace for property owners to list their properties and for travelers to conduct highly personalized searches for lodging options.

Short-term rentals offer travelers opportunities for more unique travel experiences at properties with their choice of amenities while also appealing to the notion of the sharing economy. Short-term rentals are also often a more economical choice for larger family groups that wish to stay in one house rather than split across multiple hotel rooms. In many cases, the rental host serves as a local guide, providing recommendations for dining, entertainment, and recreation.

Simone Douglas, an intern with the local Chamber of Commerce, has been asked to explore patterns in short-term rental bookings in the Santa Barbara area. The file airbnb contains a sample of the number of daily short-term rental bookings for the 731 days from July 2, 2021, to July 2, 2023. In addition, the file airbnb contains daily forecast information for July 3, 2023, to January 1, 2024. Specifically, for each of the 183 days spanning July 3, 2023, to January 1, 2024, there is a predicted number of bookings as well as a lower bound and upper bound (reflecting a 95% prediction interval for the forecast). Simone has been asked to develop data visualizations that explain the patterns in daily short-term rental bookings. Simone’s goal is to create a series of charts that display the historic short-term rental booking data and forecast information at different temporal frequencies. LO 4.5, 5.8, 6.8, 9.7 SUMMARY REPORT 1.

2.

3.

4.

5.

6.

7.

8.

Plot the time series data with a chart that displays the number of daily bookings averaged annually.

Plot the time series data with a chart that displays the number of daily bookings averaged quarterly. Plot the historic and forecasted data on the same chart.

Plot the time series data with a chart that displays the number of daily bookings averaged monthly. Plot the historic and forecasted data on the same chart.

Plot the time series data with a chart that displays the number of bookings on a daily basis. Plot the historic and forecasted data on the same chart.

Create a column chart that displays the average number of daily bookings on the seven days of the week.

Based on the five charts in parts (1)–(5), what patterns do you observe in the shortterm rental bookings?

Noting that there is not an entire year’s worth of data for 2021 and 2023, explain how the trend in the chart displaying the number of daily bookings averaged annually may be misleading.

For the chart that displays the number of daily bookings averaged quarterly, explain why there appears to be a large discrepancy between the historic data for Quarter 3 and the forecasted data for Quarter 3.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

Solution: SUMMARY REPORT •

Plot the time series data with a line chart that displays the number of daily bookings averaged annually.

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Plot the time series data with a line chart that displays the number of daily bookings averaged quarterly. Plot the historic and forecasted data on the same chart.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

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Plot the time series data with a line chart that displays the number of daily bookings averaged monthly. Plot the historic and forecasted data on the same chart.

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Plot the time series data with a line chart that displays the number of bookings on a daily basis. Plot the historic and forecasted data on the same chart.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

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Create a column chart that displays the average number of daily bookings on the seven days of the week.

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Based on the five charts in parts (1)–(5), what patterns do you observe in the shortterm rental bookings?

Higher levels of aggregation (e.g., years versus quarters, quarters versus months, months versus days) smooth the data and allow the visualization of trends and seasonality.

The line chart that displays the number of daily bookings averaged annually suggests that bookings exhibit a positive trend.

We observe seasonality in the average number of daily bookings in the charts averaged over each quarter and each month, respectively. Averaged over each quarter, the number of daily bookings displays seasonality, with bookings peaking in Quarters 2 and 3 and dipping in Quarters 1 and 4. Averaged over each month, the number of daily bookings displays seasonality, with a crest in July and a trough in January.

The chart plotting the daily number of bookings demonstrates the day-to-day fluctuations.

The column chart plotting the average number of bookings by day of the week reveals a pattern in the daily variability of bookings. Daily bookings increase from Monday to a peak on Saturday before dipping again on Sunday.

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Noting that there is not an entire year’s worth of data for 2021 and 2023, explain how the trend in the chart displaying the number of daily bookings averaged annually may be misleading.

Drilling down to the quarterly and monthly levels, specifically the chart titled “Summer Surges in Short-Term Rentals” brings to our attention that the data for 2021 only includes observations for the last two quarters of the year, and 2023 only includes

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

observations for the first two quarters of the year (plus a few days in July 2023). The following PivotTable displays the quarters and months included in each year’s data.

Thus, the positive trend at the annual level of aggregation is strongly shaped by the seasonality in the partial years’ worth of data for 2021 and 2023. We should be wary of misleading our audience by overstating the positive trend in daily bookings and monitor this as more data are collected.

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For the chart that displays the number of daily bookings averaged quarterly, explain why there appears to be a large discrepancy between the historic data for Quarter 3 and the forecasted data for Quarter 3.

© 2025 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

In the chart titled “Quarterly Seasonality in Short-Term Rentals,” the historical quarterly average for Quarter 3 in 2023 is only based on two observations (July 1 and July 2) which correspond to a relatively high number of daily rentals, presumably due to the Independence Day holiday. In contrast, the quarterly average of the forecasted daily rentals in Quarter 3 in 2023 is based on 90 observations with daily rental values that tend to decrease over the remainder of the quarter due to the seasonality. This leads to a misleading disparity between the historical data and the forecasted data at this level of aggregation. By drilling down to the monthly level for Quarter 3 in the PivotTable aggregating data at the quarterly level, we can corroborate the cause of this disparity. Furthermore, by drilling down to the monthly level for Quarter 3 n the PivotTable aggregating data at the quarterly level, the associated line chart is correspondingly modified to remedy the previous incommensurable comparison between the historical data and forecasted data.

© 2025 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

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Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann, Data Visualization - Exploring and Explaining with Data, 2nd Edition, © 2025, 9780357631348; Multi-chapter Cases

© 2025 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

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