Spreadsheet Modeling and Decision Analysis
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Course Introduction
Spreadsheet Modeling and Decision Analysis explores the use of spreadsheet software as a powerful tool for structuring, analyzing, and solving complex business problems. This course introduces students to the principles of model formulation, sensitivity analysis, and scenario planning using spreadsheets. Emphasis is placed on applying quantitative methods such as optimization, simulation, and decision analysis to support managerial decision-making in areas like finance, operations, and marketing. Through hands-on exercises and real-world case studies, students develop practical skills in building high-quality models, interpreting results, and communicating insights effectively to stakeholders.
Recommended Textbook
Practical Management Science 6th Edition by Wayne L. Winston
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Chapter 1: Introduction to Modeling
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Q1) The best strategy for implementation of a model is to involve key people in the organization in the project when the model is ready for testing and verification.
A)True
B)False
Answer: False
Q2) A completed model typically marks the end of the modeling process.
A)True
B)False
Answer: False
Q3) The primary difference between management science and business analytics is
A) management science is quantitative and business analytics is qualitative.
B) business analytics uses more current quantitative methods.
C) business analytics uses big data to solve business problems and provide insights.
D) business analytics is a subset of management science.
Answer: C
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Chapter 2: Introduction to Spreadsheet Modeling
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Q1) The NPV function takes two arguments; the discount rate and the number of time periods in the model.
A)True
B)False
Answer: False
Q2) 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.
Q3) Which of the following is a useful tool for understanding and troubleshooting a spreadsheet model
A) Data tables
B) VLOOKUP function
C) Formula auditing
D) SUMPRODUCT function
Answer: C
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Chapter 3: Introduction to Optimization Modeling
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Q1) [Part 4] Refer to Exhibit 3-1.Obtain a sensitivity report for the model in Part 1.How much should the winemaker be willing to pay for an additional labor hour
Answer: The shadow price for labor (shown below)indicates that an additional hour would increase profit by $0.625.The winemaker should be willing to pay up to this amount. 11ea5c70_d2ea_1563_945b_bf41540725d5_TB6954_00
Q2) Consider the following linear programming problem:The above linear programming problem:Maximize4x<sub>1</sub> + 2x<sub>2</sub>
Subject to:
4x<sub>1</sub> + 2x<sub>2</sub> 40
2x<sub>1</sub> + x<sub>2</sub> 20 x<sub>1</sub>,x2<sub></sub> 0
A) has only one feasible solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
Answer: C
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Chapter 4: Linear Programming Models
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Sample Questions
Q1) The results of a sensitivity analysis with a dual objective model can be shown graphically using a:
A) scatterplot
B) tradeoff curve
C) trend diagram
D) bar chart
Q2) When a workforce scheduling problem is formulated as an integer programming model,it has:
A) an integer objective function
B) integer technological coefficients
C) integer constraints
D) all of these options
Q3) Refer to Exhibit 4-2.Suppose the bonus for completing the project three months early is $250,000.What would be the net bonus to the company,after adjusting for any difference in personnel costs under the accelerated schedule
Q4) Solver does not offer a sensitivity report for models with integer constraints.
A)True
B)False
Q5) 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) The cost of an arc in a shortest path problem is not necessarily equal to the distance of the arc.
A)True
B)False
Q2) In a general logistics model that minimizes the cost of network flow,the flow balance constraint for each supply node has the form
A) Flow in Flow out + Net supply
B) Flow out Flow in + Net demand
C) Flow in = Flow out
D) Flow out Flow in + Net supply
E) Flow in Flow out + Net demand
Q3) In transportation problems,the three sets of input numbers that are required are capacities,demands and flows.
A)True
B)False
Q4) Refer to Exhibit 5-1.Suppose the shipping capacity between any two plants was limited to 2500 tons per month.Design and implement a network flow version of this model in Solver and obtain the optimal shipping plan.How much more would the shipping plan cost Sinclair in that case
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Chapter 6: Optimization Models With Integer Variables
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Q1) Refer to Exhibit 6-1.This problem is an example of what type of integer programming model
Q2) In a model with 8 changing cells,all of which are constrained to be binary,the number of potentially feasible solutions is:
A) 4
B) 8
C) 64
D) 256
Q3) Refer to Exhibit 6-3.This problem is an example of what type of integer programming model
Q4) The default integer optimality setting in Solver is:
A) 0.1%
B) 0.5%
C) 1%
D) 5%
Q5) The branch and bound algorithm uses:
A) lower bounds
B) upper bounds
C) both upper and lower bounds
D) neither upper or lower bounds
8
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Chapter 7: Nonlinear Optimization Models
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Q1) [Part 2] Refer to Exhibit 7-3.Formulate a nonlinear optimization model to find the parameters of a function of the form: f(x)= a(1 e bx)to model demand for its product as a function of ad exposures (x).In terms of fit,is this model better or worse than the model in Part 1
Explain your answer
Q2) If you try different starting values for the changing cells and obtain different solutions:
A) you can be confident there is no solution
B) there must be a mistake in your objective function
C) there must be a mistake in one of your constraints
D) you can keep the best solution you have found and hope that it is indeed optimal
Q3) A function is concave if:
A) its slope is always nondecreasing
B) a line drawn connecting two points on the curve never lies below the curve
C) its slope is always nonincreasing
D) it is always positive
Q4) [Part 1] Refer to Exhibit 7-4.Determine the minimum variance portfolio that yields an expected annual return of at least 0.10
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Chapter 8: Evolutionary Solver: An Alternative Optimization
Procedure
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Q1) 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.
Q2) Which of the following is true regarding Evolutionary Solver
A) It is efficient at handling constraints
B) A good starting is required to be successful finding a solution
C) It places more of a burden on you to specify certain parameters of the algorithm
D) Running it a second time for a problem should yield the same solution
Q3) Mutations are useful for getting a genetic algorithm "unstuck".
A)True
B)False
Q4) For a minimization problem being solved using a genetic algorithm,chromosomes that have a smaller fitness function have a lesser chance of surviving to the next generation.
A)True
B)False
Q5) Refer to Exhibit 8-4.Suppose Steve moves to Los Angeles.What is the shortest distance in this case
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) The risk profile from Precision Tree shows the probability distribution of monetary outcomes in both graphical and tabular form.
A)True
B)False
Q2) Refer to Exhibit 9-2.Should the credit union purchase the report if it costs $150
Q3) Bayes' rule is used to:
A) update the prior probabilities once new information is observed.
B) turn the given conditional probabilities (i.e. likelihoods) around.
C) update the posterior probabilities once new information is observed.
D) All of the above are uses for Bayes' rule.
Q4) Which of the following are probabilities that are conditioned on information that is obtained
A) Prior probabilities
B) Posterior probabilities
C) Marginal probabilities
D) Objective probabilities
Q5) Refer to Exhibit 9-2.What should the credit union do What is their expected profit
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Chapter 10: Introduction to Simulation Modeling
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Q1) Correlation between two random input variables may change the mean of an output,but it will not affect the variability and shape of an output distribution.
A)True
B)False
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) The three parameters required to specify a triangular distribution are the minimum,mean and maximum.
A)True
B)False
Q4) One of the primary advantages of simulation models that they enable managers to answer what-if questions about changes in systems without actually changing the systems themselves.
A)True
B)False
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Chapter 11: Simulation Models
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Q1) 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
Q2) For an NPV simulation,the value at risk (VAR)is typically defined as the:
A) 5th percentile of the NPV distribution
B) 10th percentile of the NPV distribution
C) 90th percentile of the NPV distribution
D) 95th percentile of the NPV distribution
Q3) [Part 3] Refer to Exhibit 11-2.Briefly explain why designing the plant for the expected capacity is clearly not the optimal solution.
Q4) [Part 4] Refer to Exhibit 11-2.Are there any simulations which indicated there was a chance of getting negative NPV Briefly explain in one sentence.
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) Refer to Exhibit 12-3.What percentage of all customers have to spend at least some small amount of time waiting in line
Q2) 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
Q3) The two basic modeling approaches for queuing systems are optimization and simulation.
A)True
B)False
Q4) Which of the following is not one of the types of service disciplines
A) Longest-processing-time
B) First-come-first-served
C) Service-in-random-order
D) Last-come-first-served
Q5) Refer to Exhibit 12-4.Use the M/M/s template to find the expected number of busy servers,and the expected fraction of time each server is busy
Q6) Refer to Exhibit 12-4.What percentage of customers do not wait in the queue
Page 14
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Chapter 13: Regression and Forecasting Models
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Q1) In regression analysis,we can often use the standard error of estimate se to judge which of several potential regression equations is the most useful.
A)True
B)False
Q2) Refer to Exhibit 13-2.Use the information above to estimate the linear regression model.
Q3) The percentage of variation explained R<sup>2</sup> is the square of the correlation between the observed Y values and the fitted Y values.
A)True
B)False
Q4) Which of the following is not one of the commonly used summary measures for forecast errors
A) MAE (mean absolute error)
B) MFE (mean forecast error)
C) RMSE (root mean square error)
D) MAPE (mean absolute percentage error)
Q5) Refer to Exhibit 13-3.Use a moving average model to forecast these data,requesting 4 quarters of future forecasts.Use a span of 4 quarters.
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Chapter 14: Data Mining
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Q1) See Exhibit 14.1 - What kind of person is more likely to be diagnosed with the illness
Q2) The K-Means clustering algorithm :
A) becomes an optimization model for choosing the best cluster centers.
B) determines the best value of K.
C) has an objective that maximizes the sum of the dissimilarity measures.
D) cannot be directly implemented in Excel.
Q3) See Exhibit 14-1 Use neural nets via Palisade's NeuralTools to classify the people as being diagnosed as having an illness or not. (Reserve 20% of the observations for testing.) How well does this method correctly classify people
Q4) See Exhibit 14.1 - How well can logistic regression classify the people as having the illness or not
Q5) Which of the following is not a classification method
A) Naive Bayes
B) Logistic regression
C) ROC curves
D) Neural networks
Q6) See Exhibit 14.1 - How likely would a 40 year old,200 pound father of 2 children be to have the illness
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