
Course Introduction
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Course Introduction
Business Analytics explores the systematic analysis of data to inform and improve business decision-making. This course introduces students to fundamental concepts in data collection, data visualization, statistical analysis, and predictive modeling, utilizing real-world business scenarios and case studies. Through hands-on activities with industry-standard tools, students learn to interpret data, identify trends, and generate actionable insights aimed at achieving strategic objectives. Emphasis is placed on the ethical use of data, effective communication of analytical findings, and the integration of business analytics into organizational processes.
Recommended Textbook
Practical Management Science 5th Edition by Wayne L. Winston
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Q1) A good model should achieve the right balance between being too simple and too complex.
A)True
B)False
Answer: True
Q2) In a descriptive model, the manager first wants to build a model that reflects the current situation.
A)True
B)False
Answer: True
Q3) Which of the following is not one of the desired conditions for a successful model implementation?
A)The people who will run the model understand how to enter appropriate inputs
B)The people who will run the model are able to run what-if analysis
C)The people who will run the model are able to modify it
D)The people who will run the model are able to interpret the model's outputs correctly
Answer: C
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Q1) Refer to Exhibit 2-2. Suppose instead that the company thinks it can reduce its variable cost rate. What rate would produce an NPV of $10,000?
Answer: Using Excel's Goal Seek function, the required variable cost rate would be $10.02 per unit of production.
Q2) Which of the following is not one of the features that can improve the readability of a spreadsheet model?
A)Formatting features
B)Data tables
C)Cell comments
D)Text Boxes
Answer: B
Q3) In general, any cash flow occurring at the beginning of the first time period must be placed outside the NPV function.
A)True
B)False
Answer: True
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Q1) [Part 1] Refer to Exhibit 3-2. Find an optimal solution to Western's problem. What is the production plan, and what is the total revenue?
Answer: SS = pounds of steel sheeting produced and sold = 1000
AS = pounds of aluminum sheeting produced and sold = 2000
SC = number of Standard chassis racks produced and sold = 800
DC = number of Deluxe chassis racks produced and sold = 1000
Profit = $26,200
Q2) Refer to Exhibit 3-2. What is the incremental contribution associated with adding an hour of assembly time? Over what range of increase is the marginal value valid?
Answer: Incremental contribution is $2 per hour, with an allowable increase of 25 hours.
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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Sample Questions
Q1) Solver does not offer a sensitivity report for models with integer constraints.
A)True
B)False
Q2) Refer to Exhibit 4-2. Determine the optimal staffing plan for the project.
Q3) Refer to Exhibit 4-1. Use Solver to formulate and solve the hospital's problem.
Q4) Refer to Exhibit 4-2. The project manager is evaluating options to complete the project early so that the company can earn a bonus. He has determined that the project schedule can be compressed into a six-month schedule, with the same total number of worker-months. In that case, the staffing requirements are as shown below.Develop an optimal staffing plan for the project under the accelerated schedule.
\[\begin{array} { c c c c c c c }
& { \text { Month of Project } } \\
& 1 & 2 & 3 & 4 & 5 & 6 \\
\text { Required } & 26 & 38 & 84 & 105 & 101 & 84 \end{array}\]
Q5) [Part 2] Refer to Exhibit 4-3. What happens to the revenue when the optimal plan changes to the one given in Part 1?
Q6) Refer to Exhibit 4-3. Determine the optimal processing plan for the meat market.
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Q1) Refer to Exhibit 5-3. Suppose the roads leading into and out of Krickburg are unpaved, so Steve would only be able to travel half of his usual 60 mile/hour speed on those routes. Modify the model to account for this condition. Would the shortest path change from the base case solution?
Q2) Which of the following is not an example of a condition that a more complex logistics model might include?
A)Multiple products
B)Multiple modes of transportation
C)Multiple time periods
D)Multiple objectives
Q3) A particularly useful Excel function in the formulation of transportation problems is the:
A)IF function
B)SUMIF function
C)SUMPRODUCT function
D)NPV function
Q4) 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?
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Q1) The binary variables in the fixed cost models correspond to:
A)the number of units or products produced
B)the total profit
C)the amount of labor hours
D)a process for which a fixed cost occurs
Q2) Refer to Exhibit 6-3. Suppose PharmaCo wants to have a backup for each city. What is the minimum number of representatives that can cover this region in that case? What are their home cities?
Q3) 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
Q4) The LP relaxation of an integer programming (IP) problem is typically easy to solve and provides a bound for the IP model.
A)True
B)False
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Q1) Solver is guaranteed to solve certain types of nonlinear programming models.
A)True
B)False
Q2) Which of the following is not one of the useful options within Solver's Multistart box?
A)Population size
B)Error distribution
C)Random seed
D)Upper or lower bound constraints on all changing cells
Q3) Refer to Exhibit 7-1. Suppose the company is required by regulation to charge the same price for both products. How many units of each product should the company produce in that case? What prices should it charge, to maximize profit?
Q4) Solver is guaranteed to find the global minimum (if it exists) if the objective function is concave and the constraints are linear.
A)True
B)False
Q5) [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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Q1) Refer to Exhibit 8-1. How should the train be loaded to minimize shortage and penalty costs?
Q2) Which of the following is true regarding Evolutionary Solver?
A)It is efficient at handling constraints
B)A good starting is critical to the success of it 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) The number of possible paths in a shortest path problem with n locations is:
A)n
B)n 1
C)n2
D)n!
Q4) Refer to Exhibit 8-2. Explain why this problem typically requires Evolutionary Solver to obtain a solution.
Q5) Refer to Exhibit 8-4. Formulate and solve a shortest-path model using Evolutionary Solver. What is the shortest distance Steve can travel and visit all cities? What is the route?
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Q6) Refer to Exhibit 8-3. Write out your model and interpret your results. Do the results make sense?

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Q1) The expected value of perfect information (EVPI) is a largely irrelevant concept since perfect information is almost never available at any price.
A)True
B)False
Q2) 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.
Q3) Refer to Exhibit 9-2. Construct a decision tree to help the credit union decide whether or not to make the loan. Make sure to label all decision and chance nodes and include appropriate costs, payoffs and probabilities.
Q4) Refer to Exhibit 9-2. Should the credit union purchase the report if it costs $150?
Q5) For a risk averse decision maker, the certainty equivalent is less than the expected monetary value (EMV).
A)True
B)False
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Q1) When the value of a decision variable has been optimized by running several simulations, attitude toward risk should no longer be relevant.
A)True
B)False
Q2) The RAND() function in excel models which of the following probability distributions?
A)Normal(0,1)
B)Uniform(0,1)
C)Normal( 1,1)
D)Uniform( 1,1).
Q3) Refer to Exhibit 10-2. What is the probability that the apparel company will exceed a profit at least $0.5M from the jacket line?
Q4) Refer to Exhibit 10-2. Total sales is a product of three different types of input distributions. What does the output distribution look like? What is the standard deviation of the total sales? What are the 5th and 95th percentiles of this distribution?
Q5) Refer to Exhibit 10-2. Use @RISK distributions to generate the three random variables for regional sales and derive a distribution for the total sales. What is the expected total sales?
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Q1) In cash flow models, we are typically interested in investigating:
A)the value at risk (VAR)
B)the net present value (NPV)
C)the amount of loans required to maintain a minimum cash balance
D)the interest on loans taken out by a firm
Q2) In financial simulation models, we are typically more interested in the expected NPV of a project than in the extremes of the outcomes.
A)True
B)False
Q3) [Part 1] Refer to Exhibit 11-1. What is the deterministic next present value (NPV) of the project, including the required investment, assuming a 10% discount rate?
Q4) A @RISK output range allows us to obtain a summary chart that shows the entire simulated range at once.
A)True
B)False
Q5) In warranty cost models, the key input random variable is product lifetime. A)True
B)False
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Q1) The basic economic order quantity (EOQ) model can be formulated as a linear model in Solver.
A)True
B)False
Q2) Refer to Exhibit 12-3. Suppose again that the annual demand for the sweaters is not known with certainty, but rather is estimated to be normally distributed with mean 26,000 and standard deviation 2,000. However, this time, formulate a Solver model to find the optimal (R,Q) policy to ensure that at least 99% of customer demands are met with existing inventory. What is the policy, and what is the total annual cost in that case?
Q3) Refer to Exhibit 12-1. Check your answer from Solver using the economic order quantity (EOQ) formula. Do you get the same result? Show your work.
Q4) An order cycle begins each time an order arrives and ends just before the next order arrives.
A)True
B)False
Q5) Refer to Exhibit 12-1. Assuming there are no storage costs, formulate a Solver model and find the optimal order quantity.
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Q1) [Part 1] Refer to Exhibit 13-1. Is it reasonable to assume exponentially distributed interarrival times for the grocery store customers? If so, what is ?
Q2) [Part 2] Refer to Exhibit 13-1. Assuming an exponential distribution with the parameter you obtained in Part 1, what is the probability that a customer interarrival time will be less than 2 minutes?
Q3) Traffic intensity is a very useful measure of:
A)whether the system is stable or not
B)the number of customers in a system
C)the distribution of interarrival times
D)the amount of congestion in the system
Q4) The server utilization U in an M/M/s system is always the same as the traffic intensity. A)True B)False
Q5) [Part 3] Refer to Exhibit 13-1. Again assuming an exponential distribution with the parameter you obtained in Part 2, what is the probability that a customer interarrival time will be more than 2 minutes, but less than 5 minutes?
Q6) Refer to Exhibit 13-3. What is the average length of the waiting line?
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Q1) In multiple regression, the coefficients reflect the expected change in:
A)Y when the associated X value increases by one unit
B)X when the associated Y value increases by one unit
C)Y when the associated X value decreases by one unit
D)X when the associated Y value decreases by one unit
Q2) Refer to Exhibit 14-3. Obtain a simple exponential smoothing forecast again, this time optimizing the smoothing constant. Does it make much of an improvement?
Q3) Refer to Exhibit 14-3. Use a moving average model to forecast these data, requesting 4 quarters of future forecasts. Use a span of 4 quarters.
Q4) In reference to the equation , the value 0.10 is the expected change in Y per unit change in X.
\[\hat { Y } = - 0.70 + 0.10 X\]
A)True
B)False
Q5) Refer to Exhibit 14-2. Use the information above to estimate the linear regression model.
Q6) Refer to Exhibit 14-2. Interpret each of the estimated regression coefficients of the regression model above.
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