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Microsoft Excel MBA 235

15 hours One credit

Course Description Microsoft Excel is a proprietary spreadsheet application developed by Microsoft. Its significant features include calculations, functions, graphing tools, pivot tables among others.

In the industry, Microsoft Excel has varied uses for managers like planning, estimation, budgeting, forecasting, tracking, reporting, dashboard creation and scenario analysis. Features which would help a student achieve these skills are the ones which every budding manager has to possess.

Spreadsheet programs are developed to automate tasks such as technical calculations, inferential statistics, data analysis among others. This course aims at building the skills of MBA students to effectively use Microsoft Excel as a tool while handling data as part of multiple roles they would be donning in functional areas of Production, Planning, Personnel Management, Marketing, Payroll and Accounting.

Learning Outcomes Knowledge 

Be familiar with Microsoft Excel functions that are frequently used to solve business problems.

Skills 

Identify business problems through practice exercises



Acquire hands-on skills in Excel



Find solutions with appropriate functions using Microsoft Excel



Interpret the solution and draw meaningful insights from a given scenario

Attitude 

Focus on the problem identification



Choice of right tools to handle/analyze data

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Unit I Overview of Excel

[Dataset – (hospital-charges)]

(1.5

hours) 1. Introduction to Excel Interface 2. Menu bar, Drop down menus 3. Row, Column – Height & Width – modify; Zoom – in & out sheets; 4. Introduction to dataset (Identify number of Rows, Columns); 5. Selection of cells & formatting (wrap text, merge cells); 6. Variable understanding (Create Data dictionary) ; 7. Understanding cell address; Referencing; Range; 8. Understanding the data; 9. Shortcuts a. Ctrl + up arrow – Go to top of the column; b. Ctrl + down arrow – Go to bottom of a column; c. Ctrl + right arrow – Go to end of row d. Ctrl + left arrow – Go to beginning of row e. Ctrl + Shift + up arrow – Choose all rows in a particular column to top (Try others) f. Ctrl + C – Copy g. Ctrl + V – Paste h. Ctrl + Shift + L – Filter i. Ctrl + Z – Undo (Sample: Differentiate rows state-wise) 10. Writing a problem statement; Querying the dataset __________________________________________________________________________ Unit II Formatting sheet

[Dataset – (hospital – charges)]

(3 hours)

1. Search; Find & Replace; 2. Data validation 3. Sorting & Filtering 4. Samples: (Cheapest hospital for chest pain treatment; Most expensive healthcare treatments in a particular region of the country; All hospitals in state of Alabama; All hospitals treating chest pain; Sort all states in a country alphabetically; Within each state sort all hospitals from highest to lowest cost; city wise analysis) 5. Remove $ using Find & Replace and then sort – find the answer;

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6. Text filters – And/or condition; 7. Custom sort; Multi-level sort; Samples (Prepare a report ranking providers based on cost in every district); (Which city to look at for cheap treatment for chest pain) 8. Number formatting (Bringing in same level of precision – rounding off, comma separator, currency format) 9. Conditional Formatting – Beautification of an excel sheet a. Static coloring – Using filter (Disadvantage) b. Why Conditional Formatting c. Sample (Color all cells with Average Covered Charges greater than 25000 as red) d. New rule e. Clear rule f. Copy rule g. Data bars to identify pattern (Example: Identify outliers with solid fill) h. Color scales – Relative vs Absolute (Manage rules) [E.g – compare hospitals based on pricing] i. Icon sets – Range (Numbers & Percent) j. Multiple conditional formatting (Overriding one another – with multiple scales) Exercise: Conditional Formatting In the hospital charges data set, take a column with a numeric variable (say price of a treatment). Using conditional formatting, attempt the following tasks: 1. Fill the column in any one colour (red or green) so that the highest values have darker shade of the colour and the lowest values have the lightest shades of the same colour.

2. Fill the column in red and green so that the values above a certain number (say 3000) are highlighted in a gradient of red and the ones below the number are highlighted in a gradient of green.

Is it possible to do the second task? Whether yes or no, mention how you can do that / why it cannot be done (within 100 words) 10. Advanced Conditional Formatting a. Text – Specific text containing b. Date c. Day d. Blank e. Top 5 or 10

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f. Top 5 % or 10% g. Above and below average h. Standard Deviation i. Duplicate values 11. Report making a. Formatting (colors to indicate important rows, create borders, hide unimportant data/Unhide, add/delete rows, columns, freezing rows or columns to improve readability; Both rows and columns freeze panes) b. Add page numbers, Add headers in every page c. Printing - Check print preview to adjust margins – Landscape/Portrait, Gridlines d. Convert to pdf e. Password protection and Naming files (Best Practice) _________________________________________________________________________ Unit III Data Analysis – 1 hours)

[Dataset - (bank-marketing)]

(3.5

Task: Understand measures of the variables; Univariate & Bivariate analysis 1. Types of files (Delimited, csv, tab separated) 2. Generate profiles of people who might say yes to campaign Samples – (Which customers to reach out for an e-mail marketing campaign?); (Which customers to target based on their demographics (age, marital status, balance etc))?

3. Practice creating age group from age column (formula – divide age by 10 and create buckets) 4. Practice cell references 5. Auto fill formulae 6. Use of formulae - fx 7. Logical functions – IF(), SUMIF(), COUNTIF(), AVERAGEIF(), AND(), OR()  Sample – Loan is provided if age < 40 8. Mathematical functions – SUM(), SUMPRODUCT(), COUNT(), SQRT(), POWER(), AVERAGE(), MAX(), MIN(), MEDIAN(), MODE(), STDEV(), UPPER(), LOWER() 9. Practice:  % of people who said yes/no  Replace all yes with 1 and no with 0 (Alt + A & Alt + R)

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 Do teenagers have better response rate to the campaign? Analyze and decipher.  Have married people responded better to the campaign?  What is the % response between married/unmarried and divorced? (Average IF)  Remove duplicates if any from the columns.  Practice with education, job etc.  Check whether the combination of marital status and education make an impact on response rate. (Clue: Concatenate two columns – Can use AND function);Apply conditional formatting and give your opinion.  Which top 10% of all segments would respond better for the campaign? ___________________________________________________________________________ Unit IV Data Analysis - II hours)

[Dataset – bank-marketing]

(1.5

 Working with charts – data visualization a. Practice – Plot age group with response rate in a bar chart and format the same (grid lines, legend, title) b. Explore format axis  Types of charts a. Column, Bar, Line – Two variables – One categorical another numerical (Marital status vs age) b. Stacked bars, Clustered bars – Two categorical variable (Gender vs marital status) c. Pie, Doughnut – Categorical and numerical (Tough to read – not preferred) d. Scatter – Both numerical (Age vs Income) e. Line – Trend analysis ___________________________________________________________________________ Unit V Data Analysis - III hours)

[Dataset – (bank-marketing)]

1. Pivot Table – Construction and analysis a. Sample – (Average responses– values[Convert yes – 1 & no – 0]; i. Bucket average response into marital status wise; ii. Bucket average response into job wise; Draw conclusions iii. Sort it based on the options

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(2.5

Questions: o Does it make any difference if people who are in different job roles are married or not? o Which segment to target to get a better response? o Are there any educational segments which would get better responses? o Can you get the absolute numbers instead of percentage? (Value Field settings) o Among married people, which is the “best” job type? o Can you isolate exception to the general trend? [Pockets of a particular colour surrounded by other colours in a data bar representation] Clue: Add job to rows and marital status/education to columns; Add response rates to values; Sort them based on descending order both row and column wise; Perform conditional formatting with data bars; Draw your conclusion 2. Filtering a Pivot table a. Explore job vs marital status b. Explore job vs education and draw relevant conclusions c. Which will be your target segment to get better responses Slicers: a) Can handle multiple parameters; Try with various combinations b) Try out multiple slicers with Ctrl and generate deeper insights Pivot table – Performances & Exceptions can be captured. Practice more options with the data sets provided.

3. Pivot charts with similar questions and meant for exploration. __________________________________________________________________________ Unit VI Data Analysis IV – [Data set – (bank-marketing)] hours)

(1.5

VLOOKUP – Merging of tables using a common column (four arguments)  LOOKUP_VALUE: Value to be found  TABLE_ARRAY: Table in which the LOOKUP_VALUE has to be searched  COL_INDEX_RETURN: Index of the column that has to be returned  RANGE_LOOKUP: This is an optional parameter. However, in order to ensure an exact match, always use False here Samples:  List of Jobs/Income levels – Create a sheet and look up  Try with merging two columns – marital status & education and look up for target  Try with keeping two sheets in different files (but in same directory)

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HLOOKUP - Practice ___________________________________________________________________________ Summary & Revision with additional data sets– 1.5 hours Assignment Data set to be given for assignment (20 marks)

References for e-content: 1.

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http://www.excel-easy.com/functions/cell-references.html http://www.excel-easy.com/examples/pie-chart.html http://www.excelfunctions.net/ http://www.excel-easy.com/functions/lookup-reference-functions.html http://www.excel-easy.com/data-analysis/conditional-formatting.html http://www.excel-easy.com/data-analysis/what-if-analysis.html http://www.compufield.com/advance_excel_content.html

Evaluation Pattern Assignments - 20 marks End term

- 30 marks

Data set 1 – Hospital Charges The Hospital Charges dataset has more than 150,000 records of treatment of various ailments in several US hospitals. Some stats about the dataset: (163066 rows)    

The dataset has a record of 100 ailments It has a list of 3000+ healthcare providers (hospitals, medical centres, etc.)

It has data from 50 states of the USA and approximately 2000 cities across the USA It describes the cost of treatment for approximately 7 million patients

Each record (or row) is a unique combination of state, city, ailment & provider. It also lists the average cost of treatment for a particular ailment.

Data set 2 – Bank-Marketing Objective of this telemarketing problem is to understand the types of customers which should be targeted for future marketing campaigns. The dataset contains demographic and personal information of about 45,000 people and their response to a telemarketing campaign, i.e. whether they bought a certain product when contacted by the company through telemarketing.

The objective of the problem is to find the attributes of customers who are likely to buy the product when contacted through telemarketing. This is a classic case of acquisition analytics where companies use past data to predict which customers are likely to buy certain products.

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