Data Analysis for Managers
Chapter Exam Questions
Course Introduction
Data Analysis for Managers equips students with essential skills to interpret, analyze, and draw actionable insights from business data. The course covers data collection, cleansing, and visualization, introduces fundamental statistical concepts, and applies analytical tools and software relevant to managerial decision-making. Through hands-on projects and real-world case studies, students learn to translate data findings into strategic business recommendations, enhancing their ability to make evidence-based decisions in a dynamic organizational environment.
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Practical Management Science 6th Edition by Wayne L. Winston
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Chapter 1: Introduction to Modeling
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Q1) Verification is typically the most difficult phase of the modeling process,from a mathematical perspective.
A)True
B)False
Answer: False
Q2) Which of the following is a type of model that is key to virtually every management science application
A) Heuristic model
B) Queuing model
C) Mathematical model
D) Regression model
Answer: C
Q3) Which of the following is not one of the guiding principles for a heuristic
A) Common sense
B) Intuition
C) Trial and error
D) Optimality
Answer: D
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Chapter 2: Introduction to Spreadsheet Modeling
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Q1) Refer to Exhibit 2-1.What are the two possible cases for the amount of t-shirts that will be sold to the used clothing vendor
How would you calculate this amount in a spreadsheet model
Answer: The company will either sell no t-shirts to the used clothing vendor (if it produces less than demand)or it will sell a surplus equal to the difference between production and demand (if it produces more than demand).This logic can be implemented in a spreadsheet model using an IF statement.
Q2) Goal Seek is a means for answering a large number of what-if questions quickly and easily.
A)True
B)False
Answer: False
Q3) Which of the following is not one of the components of most mathematical models
A) Inputs
B) Outputs
C) Decision variables
D) None of these options
Answer: D
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Chapter 3: Introduction to Optimization Modeling
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Q1) Linear programming models have three important properties.They are:
A) optimality, additivity and sensitivity
B) optimality, linearity and divisibility
C) divisibility, linearity and nonnegativity
D) proportionality, additivity and divisibility
Answer: D
Q2) The equation of the line representing the constraint 4x<sub>1</sub>+ 2x<sub>2</sub> 100 passes through the points:
A) (25,0) and (0,50)
B) (0,25) and (50,0)
C) ( 25,0) and (0, 50)
D) (0, 25) and ( 50,0)
Answer: A
Q3) In an optimization model,there can only be one:
A) decision variable
B) constraint
C) objective function
D) shadow price
Answer: C
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Chapter 4: Linear Programming Models
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Q1) [Part 2] Refer to Exhibit 4-3.What happens to the revenue when the optimal plan changes to the one given in Part 1
Q2) Refer to Exhibit 4-2.Determine the optimal staffing plan for the project.
Q3) In aggregate planning models,which of the following statements is correct
A) The number of workers available influences the possible production levels
B) We allow the workforce level to be modified each time period through the hiring and firing of workers
C) We eventually allow demand to be backlogged; that is, demand need not be met on time
D) All of these statements are correct.
Q4) Problems in which we must determine how to schedule employees to provide adequate service under the same situation each planning period are referred to as:
A) static scheduling problem
B) dynamic scheduling problem
C) transportation scheduling problem
D) All of these options
Q5) Refer to Exhibit 4-1.Use Solver to formulate and solve the hospital's problem.
Q6) Refer to Exhibit 4-3.Determine the optimal processing plan for the meat market.
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Chapter 5: Network Models
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Q1) For all routes with positive flows in an optimized transportation problem,the reduced cost will be:
A) zero
B) how much less shipping costs would have to be for shipments to occur along that route
C) how much more shipping costs would have to be for shipments to occur along that route
D) how much the capacity is along that shipping route
Q2) Refer to Exhibit 5-3.Implement the appropriate model in Solver and determine the shortest path for Steve.How many total miles will he travel on his trip
Q3) The objective in transportation problems is typically to:
A) maximize profits
B) maximize revenue
C) minimize costs
D) maximize feasibility
Q4) In transportation problems,shipments between supply points or between demand points are possible.
A)True
B)False
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Chapter 6: Optimization Models With Integer Variables
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Q1) Rounding the solution of a linear programming to the nearest integer values provides an:
A) integer solution that is optimal
B) integer solution that is not optimal
C) integer solution that might be optimal
D) infeasible solution
Q2) The branch and bound algorithm uses:
A) lower bounds
B) upper bounds
C) both upper and lower bounds
D) neither upper or lower bounds
Q3) Refer to Exhibit 6-2.Suppose the shipping capacity for all routes is 3000 tons per month.What is Sinclair's optimal shipping plan in that case
What is the total cost in that case
Q4) Many inherently nonlinear problems can be transformed into linear models with the use of:
A) integer variables
B) integer constraints
C) binary variables
D) binary constraints
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Chapter 7: Nonlinear Optimization Models
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Q1) As an objective,minimizing the sum of squared errors is equivalent to minimizing the A) root mean square error
B) weighted sum of squared errors
C) sum of absolute errors
D) maximum absolute error
Q2) In advertising response models,a typical source of nonlinearity is a decreasing marginal effect,where each extra ad gains fewer exposures than the previous ad.
A)True
B)False
Q3) A function is convex if a line drawn connecting two points on the curve never lies below the curve.
A)True
B)False
Q4) The sum of two concave functions is concave.
A)True
B)False
Q5) Refer to Exhibit 7-1.How many units of each product should the company produce What prices should it charge,to maximize profit
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Chapter 8: Evolutionary Solver: An Alternative Optimization
Procedure
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Q1) If you let a genetic algorithm run long enough,it is guaranteed to find the solution to any optimization problem.
A)True
B)False
Q2) A traveling salesman problem with a starting city and 10 other cities that must be visited has 1,826,800 possible solutions.
A)True
B)False
Q3) Refer to Exhibit 8-2.Explain why this problem typically requires Evolutionary Solver to obtain a solution.
Q4) The number of possible paths in a shortest path problem with n locations is:
A) n
B) n 1
C) n<sup>2</sup>
D) n!
Q5) Refer to Exhibit 8-3.Given that the unit cost of the gourmet snack is $2.50,use a two-part tariff price model and evolutionary solver to determine the best pricing strategy.
Q6) Refer to Exhibit 8-1.This is an example of what type of optimization problem
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Chapter 9: Decision Making Under Uncertainty
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Q1) Refer to Exhibit 9-1.Construct a decision tree to help the farmer make his decision.What should he do Explain your answer.
Q2) The denominator of Bayes' rule:
A) is the same as the simple probability of an outcome O.
B) decomposes the probability of the new information I into all possibilities.
C) is sometimes called the law of complementary probabilities.
D) is unique for each possible outcome.
Q3) The strategy region graph is a type of sensitivity analysis chart that:
A) is useful in determining whether the optimal decision changes over the range of the input variable.
B) ranks the sensitivity of the EMV to the input variables.
C) reflects how the value of information changes over a range of probabilities.
D) None of these
Q4) For a risk averse decision maker,the certainty equivalent is less than the expected monetary value (EMV).
A)True
B)False
Q5) Refer to Exhibit 9-2.Should the credit union purchase the report if it costs $150
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Chapter 10: Introduction to Simulation Modeling
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Q1) Refer to Exhibit 10-2.Suppose the jacket sales price also varies,depending on the individual retailers and their pricing strategies.Assume that sales price is normally distributed with a mean of $65 per unit and a standard deviation of $10.How much revenue will the jacket line produce (ignore discounting)
Q2) Excel's standard functions,along with the RAND function,can be used to generate random numbers from many different types of probability distributions.
A)True
B)False
Q3) A correlation matrix must always have 1's along its diagonal (because a variable is always perfectly correlated with itself)and numbers between 1 and +1 elsewhere.
A)True
B)False
Q4) A common guideline for constructing a 95% confidence interval is to place upper and lower bounds one standard error on either side of the mean.
A)True
B)False
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Chapter 11: Simulation Models
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Q1) A common distribution for modeling product lifetimes is the normal distribution
A)True
B)False
Q2) Which of the following functions is not an @RISK statistical function
A) RISKMIN
B) RISKMAX
C) RISKPERCENTILE
D) RISKSIMTABLE
Q3) [Part 1] Refer to Exhibit 11-2.Perform a simulation assuming the plant will be designed to meet the expected demand.What is the net present value (NPV)in that case
Q4) Which of the following @RISK functions can be used to find the probability of a particular value in an output distribution
A) RISKMIN
B) RISKMAX
C) RISKPERCENTILE
D) RISKTARGET
Q5) [Part 3] Refer to Exhibit 11-1.What is the standard deviation of the NPV What does it indicate
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Chapter 12: Queueing Models
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Q1) Which of the following is not one of the important issues defining types of arrivals in a queuing system
A) Whether customers arrive one at a time or in batches.
B) Whether customers are all essentially alike or are in separate priority classes.
C) Whether customers have been through the system before or not
D) Whether customers will wait in line or not
Q2) Refer to Exhibit 12-3.What is the average length of time (in hours)spent waiting in line
Q3) Server utilization is the:
A) amount of time a typical server is busy
B) fraction of time a typical server is busy
C) number of servers being used in a system
D) number of times a server is used in a system
Q4) The two basic modeling approaches for queuing systems are optimization and simulation.
A)True
B)False
Q5) Refer to Exhibit 12-2.How many of the servers are busy on average
Q6) Refer to Exhibit 12-4.What percentage of customers do not wait in the queue
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Chapter 13: Regression and Forecasting Models
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Q1) Refer to Exhibit 13-1.How does the R<sup>2</sup> value for this multiple regression model compare to that of the simple regression model estimated above Interpret the adjusted R<sup>2</sup> values for the two models.
Q2) Refer to Exhibit 13-3.Obtain a simple exponential smoothing forecast again,this time optimizing the smoothing constant.Does it make much of an improvement
Q3) Refer to Exhibit 13-3.Obtain a time series chart.Which of the forecasting models (one or more)do you think should be used for forecasting based on this chart Why
Q4) A time series can consist of four different components: trend,seasonal,cyclical,and random (or noise).
A)True
B)False
Q5) Refer to Exhibit 13-2.Identify and interpret the percentage of variation explained (R<sup>2</sup>)for the model.
Q6) Refer to Exhibit 13-1.Estimate a simple linear regression model involving shipping cost and package weight.Interpret the slope coefficient of the least squares line as well as R<sup>2</sup>.
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Chapter 14: Data Mining
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Q1) Which of the following is false concerning a data warehouse
A) It is designed to study patterns in data.
B) It combines data from multiple sources.
C) It allows follow up responses to questions.
D) It supports the daily operations of the company.
Q2) The function INDEX(A1:E5,4,3)would return the value in cell C4.
A)True B)False
Q3) If the probability of a restaurant being successful is 10% then the odds of it failing are 10 to 1.
A)True B)False
Q4) See Exhibit 14.1 - How likely would a 40 year old,200 pound father of 2 children be to have the illness
Q5) See Exhibit 14.1 - How well can logistic regression classify the people as having the illness or not
Q6) In data partitioning,data can be divided into training,testing,and prediction subsets.
A)True
B)False
Page 16
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