Practical Management Science 6th Edition By Wayne L. Winston, S Christian Albright Test Bank

Chapter 1 - Introduction to Modeling True / False 1. Models that suggest a desirable course of action are called descriptive models a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.1 Introduction OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 2. In modeling situations where it is not possible to write an equation for an output in terms of the inputs, there may still be a mathematical procedure for calculating outputs from inputs. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.1 Introduction OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 3. In a descriptive model, the manager first wants to build a model that reflects the current situation. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 4 Model Verification OTHER: BUSPROG-Analytic DISC- Mathematical Modeling Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 4. One of the advantages of spreadsheet models is that they allow managers to ask what-if questions. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.2 A Capital Budgeting Example - An Optimization Model OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 5. One of the arguments that management science practitioners have used to criticize the emphasis on specific models is that they do not provide the correct answer. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.3 Modeling Versus Models OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 6. The overall modeling process typically done in practice always requires seven steps: define the problem, collect and summarize data, develop a model, verify the model, select one or more suitable decisions, present the results to the organization, and finally implement the model and update it through time. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling TOPICS: 1.1 Introduction OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 7. Modeling is a process where the essence of a theoretical problem is extracted into a model, spreadsheet or otherwise. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 1 Problem Definition OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 8. In some applications, an analyst might present several alternative solutions from a model, and let the organization choose the best one. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 3 Model Development OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 9. A management science model is typically initiated when an organization believes it has a problem. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 4 Model Verification OTHER: BUSPROG-Analytic DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 10. Data are often not in the required form, in which case it is the analysts' job to gather the right data and put it into an appropriate format. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 3 Model Development OTHER: BUSPROG-Analytic DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 11. A good model should achieve the right balance between being too simple and too complex. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 4 Model Verification OTHER: BUSPROG-Analytic DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 12. Verification is typically the most difficult phase of the modeling process, from a mathematical perspective. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 5 Optimization and Decision Making OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 13. As models become larger and more complex, heuristic solutions are often adequate, even though they are not necessarily optimal solutions. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 7 Model Implementation OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 14. 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 POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 7 Model Implementation OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 15. A completed model typically marks the end of the modeling process. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 1.6 Why Study Management Science?

OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM Multiple Choice 16. 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 POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.2 A Capital Budgeting Example - A Descriptive Model OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 17. Which of the following is not one of advantages of mathematical models? a. Mathematical models enable managers to understand the problem better b. Mathematical models allow analysts to employ a variety of mathematical solution procedures c. The mathematical modeling process itself, if done correctly, often helps "sell" the solution d. Mathematical models help reduce the cost of obtaining a solution ANSWER: d POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 3 Model Development OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling 18. Before trusting the answers to what-if scenarios from a spreadsheet model, a manager should attempt to: a. validate the model b. make sure all possible scenarios have been investigated c. check the mathematics in the model d. sense-check the model ANSWER: a POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.2 A Capital Budgeting Example - A Descriptive Model OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 19. Optimization models are useful for determining: a. sensitivity to inputs b. whether the inputs are valid or not c. what the manager should do d. the value of the output under the current conditions ANSWER: c POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - The Model as a Beginning, Not an End OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 20. Management science has often been taught as a collection of: a. theories b. problems c. models d. topics ANSWER: c POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling HAS VARIABLES: False TOPICS: 1.6 Why Study Management Science?

OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 21. 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 POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 22. Defining an organization's problem includes: a. specifying the organization's objectives b. collecting the organization's historical data c. defining the model of the problem d. sensitivity analysis ANSWER: a POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.3 Modeling Versus Models OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 23. Which of the following type of model is used when inputs are modeled with probability distributions? a. Simulation model b. Deterministic model c. Heuristic model d. Spreadsheet model Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling ANSWER: POINTS: DIFFICULTY:

a 1 Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 5 Optimization and Decision Making OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 24. A first step in determining how well a model fits reality is to: a. check whether the inputs are correct b. see if the sensitivity analysis is correct c. check whether the model is valid for the current situation d. try some what-if scenarios to see if the model is able to obtain solutions ANSWER: c POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 1 Problem Definition OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 25. Which of the following is not necessarily a property of a good model? a. The model represents the client's real problem accurately b. The model is as simple as possible c. The model is based on a well-known algorithm d. The model is one the client can understand ANSWER: c POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 2 Data Collection OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling 26. Which of the following is a possible cause if a model's outputs for certain inputs are not as expected? a. The certain inputs may not be correct b. The model could be too detailed of an approximation of the actual situation c. The mathematics in the model are inadequate d. The analyst's expectations are not correct ANSWER: d POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 3 Model Development OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 27. 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 POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 4 Model Verification OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 28. 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 POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension Copyright Cengage Learning. Powered by Cognero.

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Chapter 1 - Introduction to Modeling QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 5 Optimization and Decision Making OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 29. The most frequent cause of a failed implementation of a model is: a. the model is incorrect b. the analyst fails to communicate how to use the model c. the data for the model is unavailable d. the model is too complex ANSWER: b POINTS: 1 DIFFICULTY: Moderate Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 6 Model Communication to Management OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM 30. Which of the following is not one of the reasons for the new-found relevance of management science models? a. Modeling is an important way to think about problems in general b. Modeling is often now a legal requirement c. The business world is increasingly driven by numbers d. Modeling helps develop intuition for problems ANSWER: b POINTS: 1 DIFFICULTY: Easy Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 1.4 A Seven Step Modeling Process - Step 7 Model Implementation OTHER: BUSPROG-Communication DISC- Mathematical Modeling DATE CREATED: 5/17/2017 3:39 PM DATE MODIFIED: 10/21/2017 8:35 PM

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Chapter 2 - Introduction to Spreadsheet Modeling True / False 1. Much of the power of spreadsheet models derives from their flexibility. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.2. Basic Spreadsheet Modeling: Concepts and Practices OTHER: BUSPROG- Communication DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 2. A shortcut for establishing absolute references is pressing the F9 key. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.2. Basic Spreadsheet Modeling: Concepts and Practices OTHER: BUSPROG- Communication DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 3. A chart is typically much more informative to a business manager than the table of numbers it is based on. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.4 Breakeven Analysis - Forming a One Way Data Table OTHER: BUSPROG- Analytic DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 4. Many models are built for the purpose of permitting experimentation with various scenarios.

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Chapter 2 - Introduction to Spreadsheet Modeling a. True b. False ANSWER: POINTS: DIFFICULTY:

True 1 Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.4 Breakeven Analysis - Using Goal Seek OTHER: BUSPROG- Analytic DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 5. Goal Seek is a means for answering a large number of what-if questions quickly and easily. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.4 Breakeven Analysis - Using the Formula Auditing Tool OTHER: BUSPROG- Analytic DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 6. In Excel terminology, the unknown value used in Goal Seek is called the input cell. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.5 Ordering with Quantity Discounts and Demand Uncertainty - Excel Function: Vlookup OTHER: BUSPROG- Analytic DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 7. Trace Dependents and Trace Precedents are Formula Auditing commands. a. True b. False Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling ANSWER: POINTS: DIFFICULTY:

True 1 Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.6 Estimating the Relationship Between Price and Demand OTHER: BUSPROG- Communication DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 8. The NPV function takes two arguments; the discount rate and the number of time periods in the model. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.6 Estimating the Relationship Between Price and Demand OTHER: BUSPROG- Communication DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 9. 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 POINTS: 1 DIFFICULTY: Challenging |Bloom's Knowledge Challenging |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.6 Estimating the Relationship Between Price and Demand OTHER: BUSPROG- Analytic DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 10. The HLOOKUP function works exactly the same as the VLOOKUP function, except the lookup table is arranged in columns instead of rows. a. True b. False ANSWER: False POINTS: 1 Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling DIFFICULTY:

Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 2.6 Estimating the Relationship Between Price and Demand OTHER: BUSPROG- Communication DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM Multiple Choice 11. 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 POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.2. Basic Spreadsheet Modeling: Concepts and Practices OTHER: BUSPROG- Communication DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 12. 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 POINTS: 1 DIFFICULTY: Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.3 Cost Projections - Developing the Spreadsheet Model OTHER: BUSPROG- Communication DISC- Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 13. Which of the following is a useful tool for investigating what-if questions? a. Data tables Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling b. VLOOKUP function c. Formula auditing d. SUMPRODUCT function ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.3 Cost Projections - Developing the Spreadsheet Model OTHER: BUSPROG- Communication DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 14. The Excel tool for solving one equation with one unknown is: a. Solver b. Goal Seek c. Trend function d. NPV function ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.3 Cost Projections - Using the Model for What If Questions OTHER: BUSPROG- Communication DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 15. 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 POINTS: 1 DIFFICULTY: Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.4 Breakeven Analysis - Using Goal Seek OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling DATE MODIFIED: 10/21/2017 8:36 PM 16. Which of the following is not one of the required arguments for a VLOOKUP function? a. The lookup table range b. The value you want to compare to the values in the left column of the table c. The index of the column you want the returned value to come from d. TRUE (for an approximate match) or FALSE (for an exact match) ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.4 Breakeven Analysis - Using Goal Seek OTHER: BUSPROG- Communication DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 17. Estimating the relationships between variables in a spreadsheet model can be done using: a. data tables b. Goal Seek c. the VLOOKUP function d. curve fitting ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.4 Breakeven Analysis - Using the Formula Auditing Tool OTHER: BUSPROG- Communication DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 18. Which of the following is not one of the types of curve fitting models available in Excel's Trendline tool? a. Exponential b. Linear c. Interpolation d. Power ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Knowledge Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling HAS VARIABLES: False TOPICS: 2.7 Decisions Involving the Time Value of Money - Solution OTHER: BUSPROG- Communication DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 19. An important property of the exponential function is that: a. if x changes by 1 unit, then y changes by a constant percentage that is approximately equal to the model constant b times 100% b. if x changes by 1 unit, then y changes by a constant percentage that is approximately equal to the model constant b% c. if x changes by 1%, then y changes by a constant percentage that is approximately equal to the model constant b times 100% d. if x changes by 1%, then y changes by a constant percentage that is approximately equal to the model constant b% ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.7 Decisions Involving the Time Value of Money - Solution OTHER: BUSPROG- Communication DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM 20. To evaluate which of a set of curves fits the data best, we can use: a. APE b. MAPE c. R2 d. NPV ANSWER: POINTS: DIFFICULTY:

b 1 Easy |Bloom's Knowledge Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 2.5 Ordering with Quantity Discounts and Demand Uncertainty - Excel Function: Vlookup OTHER: BUSPROG- Communication DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:36 PM Subjective Short Answer Exhibit 2-1 Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling A t-shirt company is planning a production run for an event where the attendance (and thus demand for t-shirts) is uncertain. The event planners have indicated that they think the attendance will be 500, 750 or 1000, with probabilities of 30%, 50% and 20% respectively. The company must pre-order the blank t-shirts (cost=$5 per shirt) and it can sell finished shirts for $12 apiece. Any finished shirts that cannot be sold at the event can be sold for $2 apiece to a used clothing vendor.

21. Refer to Exhibit 2-1. What Excel function is useful for calculating the expected value of demand for t-shirts? What is the expected demand?

ANSWER: The SUMPRODUCT function is useful for multiplying the respective probabilities times the demand outcomes and summing the products. The expected value is 725.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-1 TOPICS: 2.5 Ordering with Quantity Discounts and Demand Uncertainty - Developing the Spreadsheet Model OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM 22. Refer to Exhibit 2-1. What Excel function is useful for calculating revenue? Explain why it is useful.

ANSWER: The IF function is useful for calculating revenue. This because there are two difference cases; demand could exceed production, in which case only the amount produced can be used to calculate revenue, and demand could be less than production, in which case only the demand can be used to calculate revenue.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-1 TOPICS: 2.2 Basic Spreadsheet Modeling: Concepts and Best Practices - Excel Function IF OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM 23. 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.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-1 TOPICS: 2.2 Basic Spreadsheet Modeling: Concepts and Best Practices - Excel Function IF OTHER: BUSPROG- Analytic Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM 24. Refer to Exhibit 2-1. Suppose that blank t-shirts can only be ordered from the wholesale vendor in batches of 100?

How many t-shirts should the company order?

ANSWER: We can set up a one-way data table with net profit as the output and order as the input (with trial quantities of 500, 600, 700, 800, 900, and 1000), which shows that the net profit is maximized at $4900 with an order of 700 shirts.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-1 TOPICS: 2.4 Breakeven Analysis - Forming a One Way Data Table OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM 25. Refer to Exhibit 2-1. Suppose now that blank t-shirts can only be ordered from the wholesale vendor in batches of 50?

How many t-shirts should the company order?

ANSWER: We can again set up a one-way data table with net profit as the output and order as the input (with trial quantities of 600, 650, 700, 750, and 800), which shows that the net profit is maximized at $5000 with an order of 750 shirts.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-1 TOPICS: 2.4 Breakeven Analysis - Forming a One Way Data Table OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM Exhibit 2-2 A small sporting goods company is considering investing $2000 in a project at the start of year 1 that will produce volleyballs over the next five years. The company plans to produce and sell 200 volleyballs in the first year, and expects that volume to grow by 10% each year thereafter. The unit selling price forecast the company has developed is $20 in year 1, $22 in year 2, $25 in year 3, $28 in year 4, and $31.50 in year 5. Variable costs are forecast to be $15 per unit produced, and there will be a fixed overhead cost in each year of $500. (Unless otherwise indicated, assume that all cash flows occur at the end of the year.)

26. Refer to Exhibit 2-2. Use the above information to develop a simple cash flow proforma sheet, and then apply Excel's NPV function to calculate the project value assuming a 10% discount rate. What is your answer?

ANSWER: The project NPV is $5,468.24 (allowing for a fraction of a volleyball) POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-2 TOPICS: 2.7 Decisions Involving the Time Value of Money - Solution OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM 27. Refer to Exhibit 2-2. Suppose the company thinks it may be able to produce and sell more than currently planned.

What growth rate of production would produce an NPV of $10,000?

ANSWER: Using Excel's Goal Seek function, the required growth rate would be 27.4% per year.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-2 TOPICS: 2.4 Breakeven Analysis - Using Goal Seek OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM 28. 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.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-2 TOPICS: 2.4 Breakeven Analysis - Using Goal Seek OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM 29. [Part 1] Refer to Exhibit 2-2. Use the graphing function in Excel to construct a scatterplot of forecasted price versus time, and fit a linear trendline to the data. What are the coefficients of the linear model, and what is the MAPE of a linear model forecast, compared to the company's forecast?

ANSWER: The linear trend fit produces an intercept of 16.6 and a slope of 2.9. Forecasting with this model and comparing against the company forecast results in a MAPE of 1.5%.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-2 Copyright Cengage Learning. Powered by Cognero.

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Chapter 2 - Introduction to Spreadsheet Modeling TOPICS: 2.6 Estimating the Relationship Between Price and Demand OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM 30. [Part 2] Refer to Exhibit 2-2. Use the same scatterplot constructed for the previous question, fit an exponential trendline to the data. What are the coefficients of the exponential model, and what is the MAPE of an exponential model forecast, compared to the company's forecast?

ANSWER: The exponential model fit produces a constant of 17.684 and an exponent of 0.115. Forecasting with this model and comparing against the company forecast results in a MAPE of 0.47% POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 02-2 TOPICS: 2.6 Estimating the Relationship Between Price and Demand OTHER: BUSPROG- Analytic DATE CREATED: 5/17/2017 3:44 PM DATE MODIFIED: 10/21/2017 8:11 PM

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Chapter 3 - Introduction to Optimization Modeling 1. In an optimization model, there can only be one: a. decision variable b. constraint c. objective function d. shadow price ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.2 Introduction to Optimization OTHER: BUSPROG- Communication DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 2. In using Excel to solve linear programming problems, the changing variable cells represent the: a. value of the objective function b. constraints c. decision variables d. total cost of the model ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.2 Introduction to Optimization OTHER: BUSPROG- Communication DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 3. The condition of nonnegativity requires that: a. the objective function cannot be less that zero b. the decision variables cannot be less than zero c. the right hand side of the constraints cannot be greater then zero d. the reduced cost cannot be less than zero ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.2 Introduction to Optimization OTHER: BUSPROG- Communication DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling 4. If a manufacturing process takes 4 hours per unit of x1 and 2 hours per unit of x2 and a maximum of 100 hours of manufacturing process time are available, then an algebraic formulation of this constraint is: a. 4x1 + 2x2 ≥ 100 b. 4x1 − 2x2 ≤ 100 c. 4x1 + 2x2 ≤ 100 d. 4x1 − 2x2 ≥ 100 ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.3 A Two-Variable Project Mix Model - An Algebraic Model OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 5. The feasible region in all linear programming problems is bounded by: a. corner points b. hyperplanes c. an objective line d. all of these options ANSWER: b POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.3 A Two-Variable Project Mix Model - A Graphical Solution OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 6. Suppose a company sells two different products, x1 and x2, for net profits of $6 per unit and $3 per unit, respectively.

The slope of the line representing the objective function is: a. 0.5 b. −0.5 c. 2 d. −2 ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling TOPICS: 3.3 A Two-Variable Project Mix Model - A Graphical Solution OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 7. The equation of the line representing the constraint 4x1 + 2x2 ≤ 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 POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.3 A Two-Variable Project Mix Model - A Graphical Solution OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 8. When the profit increases with a unit increase in a resource, this change in profit will be shown in Solver's sensitivity report as the: a. add-in price b. sensitivity price c. shadow price d. additional profit ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.3 A Two-Variable Project Mix Model - A Graphical Solution OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 9. 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 POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.5 Properties of Linear Models OTHER: BUSPROG- Communication DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 10. Consider the following linear programming problem: Maximize 4x1 + 2x2 Subject to: 4x1 + 2x2 ≤ 40 2x1 + x2≥ 20 x1, x2 ≥ 0 The above linear programming problem: a. has only one feasible solution b. has more than one optimal solution c. exhibits infeasibility d. exhibits unboundedness ANSWER: c POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 3.6 Infeasibility and Unboundedness - Infeasibility OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 11. All linear programming problems should have a unique solution, if they can be solved. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.2 Introduction to Optimization OTHER: BUSPROG- Communication DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 12. When formulating a linear programming spreadsheet model, there is a set of designated cells that play the role of the decision variables. These are called the changing variable cells. a. True Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.2 Introduction to Optimization OTHER: BUSPROG- Communication DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 13. The feasible region in a graphical solution of a linear programming problem will appear as some type of polygon, with lines forming all sides. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.3 A Two-Variable Project Mix Model - A Graphical Solution OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 14. If the objective function has the equation {4x1 + 2x2}, then the slope of the objective function line is −2. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.3 A Two-Variable Project Mix Model - An Algebraic Model OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 15. If a constraint has the equation 5x1 + 2x2 ≤ 60, then the constraint line passes through the points (0,12) and (30,0). a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.3 A Two-Variable Project Mix Model - An Algebraic Model OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 16. Shadow prices are associated with nonbinding constraints, and show the change in the optimal objective function value when the right side of the constraint equation changes by one unit. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.4 Sensitivity Analysis - Shadow Prices OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 17. Suppose the allowable increase and decrease for an objective coefficient of a decision variable that has a current value of $50 are $25 (increase) and $10 (decrease). If the coefficient were to change from $50 to $65, the optimal value of the objective function would not change. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Evaluation QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.4 Sensitivity Analysis OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 18. Suppose the shadow price for a constraint is $12 and the allowable increase and decrease for the right hand side of the constraint are 25 (increase) and 10 (decrease). If the right hand side of that constraint were to increase by 10 the shadow price changes. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Evaluation QUESTION TYPE: True / False Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling HAS VARIABLES: False TOPICS: 3.4 Sensitivity Analysis OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 19. The proportionality property of LP models implies that the sum of the contributions from the various activities to a particular constraint equals the total contribution to that constraint. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Evaluation QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.5 Properties of Linear Models - Proportionality OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 20. Common errors in LP models that exhibit unboundedness are a constraint that has been omitted or an input which is incorrect. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Evaluation QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 3.6 Infeasibility and Unboundedness - Unboundedness OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM Exhibit 3-1 A winemaker in California's Napa Valley must decide how much of two types of wine she will produce from a particular variety of grapes. Each liter of table wine yields $8 profit, while each liter of dessert wine produces $3 profit. The labor hours and bottling process time used for type of wine are given in the table below. Resources available include 200 labor hours and 80 hours of bottling process time. Assume the winemaker has more than enough grapes available to supply any feasible production plan.

Labor (Hours) Process Time (Hours)

Table 0.20 0.30

Dessert 0.60 0.10

21. [Part 1] Refer to Exhibit 3-1. Formulate a linear programming model that will enable the winemaker to determine the Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling number of liters of each type of wine to produce in order to maximize her profit.

ANSWER: Let x1 = liters of table wine and x2 = liters of dessert wine. The linear programming model to maximize the profit is: Maximize Subject to:

8x1 + 3x2 0.2x1 + 0.6x2 ≤ 200 0.3x1 + 0.1x2 ≤ 80 x1, x2 ≥ 0

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-1 TOPICS: 3.3 A Two-Variable Project Mix Model - An Algebraic Model OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 22. [Part 2] Refer to Exhibit 3-1. Using the graphical solution method, find an optimal solution to the model in Part 1 and determine the maximum profit.

ANSWER: The optimal solution is (x1, x2) = (175,275), and the maximum profit is $2,225.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-1 TOPICS: 3.3 A Two-Variable Project Mix Model - A Graphical Solution OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 23. [Part 3] Refer to Exhibit 3-1. Implement the model in Part 1 in Excel Solver and obtain an answer report. Which constraint(s) are binding on the optimal solution?

ANSWER: The constraints section of the answer report (below) shows that the labor and process constraints are binding.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling HAS VARIABLES: False PREFACE NAME: Exhibit 03-1 TOPICS: 3.4 Sensitivity Analysis - Solver's Sensitivity Report OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 24. [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.

POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-1 TOPICS: 3.4 Sensitivity Analysis - Solver's Sensitivity Report OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 25. [Part 5] Refer to Exhibit 3-1. Suppose the winemaker can obtain 100 addition labor hours. Can you use the sensitivity analysis obtained for Part 4 to determine her expected profit? Would her bottling plan change? Explain your answer.

ANSWER: Using the shadow price for labor, her profit would increase by $0.625*100=$62.5. The 100 extra hours are within the allowable increase, and would enable her to bottle considerably more (462.5 liters) desert wine, while still making 112.5 liters of table wine.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-1 TOPICS: 3.4 Sensitivity Analysis - Solver's Sensitivity Report OTHER: BUSPROG- Analytic DISC- Optimization Modeling Copyright Cengage Learning. Powered by Cognero.

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Chapter 3 - Introduction to Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM Exhibit 3-2 Western Chassis produces high-quality polished steel and aluminum sheeting and two lines of industrial chassis for the rack mounting of Internet routers, modems, and other telecommunications equipment. The contribution margin (contribution toward profit) for steel sheeting is $0.40 per pound and for aluminum sheeting is $0.60 per pound. Western earns $12 contribution on the sale of a Standard chassis rack and $15 contribution on a Deluxe chassis rack. During the next production cycle, Western can buy and use up to 25,800 pounds of raw unfinished steel either in sheeting or in chassis. Similarly, 20,400 pounds of aluminum are available. One standard chassis rack requires 16 pounds of steel and 8 pounds of aluminum. A Deluxe chassis rack requires 12 pounds of each metal. The output of metal sheeting is restricted only by the capacity of the polisher. For the next production cycle, the polisher can handle any mix of the two metals up to 4,000 pounds of metal sheeting. Chassis manufacture can be restricted by either metal stamping or assembly operations; no polishing is required. During the cycle no more than 2,500 total chassis can be stamped, and there will be 920 hours of assembly time available. The assembly time required is 24 minutes for the Standard chassis rack and 36 minutes for the Deluxe chassis rack. Finally, market conditions limit the number of Standard chassis racks sold to no more than 1,200 Standard and no more than 1,000 Deluxe. Any quantities of metal sheeting can be sold.

26. [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 POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-2 TOPICS: 3.7 A Larger Product Mix Model - Developing the Spreadsheet Model OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 27. [Part 2] Refer to Exhibit 3-2. Obtain a sensitivity report for the solution reported in Part 1. Which constraints are binding?

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Chapter 3 - Introduction to Optimization Modeling ANSWER:

Steel available, Aluminum available, Assembly SS, and Market Deluxe SS all have nonzero shadow prices, so they are binding.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-2 TOPICS: 3.4 Sensitivity Analysis - Solver's Sensitivity Report OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 28. 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.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-2 TOPICS: 3.4 Sensitivity Analysis - Solver's Sensitivity Report OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 29. Refer to Exhibit 3-2. What is the value of additional capacity on the polisher? How much increase and decrease in this capacity is possible before a change occurs in the optimal production schedule?

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Chapter 3 - Introduction to Optimization Modeling ANSWER:

The value of additional capacity on the polisher is zero, since it is not binding. The allowable increase is unbounded, and the allowable decrease is 1000.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-2 TOPICS: 3.4 Sensitivity Analysis - Solver's Sensitivity Report OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM 30. Refer to Exhibit 3-2. An advertising agency has devised a marketing plan for the Western Chassis Company that will increase the market for Deluxe chassis. The plan will increase demand by 75 Deluxe chassis per month at a cost of $100 per month. Should Western adopt the plan? Briefly explain why.

ANSWER: The change in the profit would be $1.8/hour shadow price times 75 hours, or $135, so Valley should adopt the plan.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 03-2 TOPICS: 3.4 Sensitivity Analysis - Solver's Sensitivity Report OTHER: BUSPROG- Analytic DISC- Optimization Modeling DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:35 PM

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Chapter 4 - Linear Programming Models 1. An advertising model in which we try to determine how many excess exposures we can get at different given budget levels is an example of a: a. static optimization model b. dynamic optimization model c. dual objective model d. multiple constraint model ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.2 Advertising Models - A Dual Objective Extension of the Model OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 2. 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 ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.2 Advertising Models - A Dual Objective Extension of the Model OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 3. 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 ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 4. 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 ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 5. Workforce scheduling problems in which the worker schedules continue week to week are: a. continuous problems b. transition problems c. integrated problems d. wraparound problems ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 6. If the following represents decision variables for the number of hours employee i works in week j ,

then to indicate that the number of working hours of 4 employees in week 3 should not exceed 160 hours, we must have Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models the constraint a. the cell in row 3 column 4 must be <= 160 b. the sum of the column 1 cells must be <= 160 c. the sum of the row 3 cells must be <= 160 d. the sum of the column 3 cells must be <= 160 ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 7. 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.

ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.4 Aggregate Planning Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 8. Which of the following statements is a type of constraint that is often required in blending problems? a. Integer constraint b. Binary constraint c. Quality constraint d. None of these options ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.5 Blending Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models 9. The constraints in a blending problem can be specified in an intuitive way and still lead to which of the following problems? a. Unboundedness b. Infeasibility c. Nonlinearity d. None of these options ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.5 Blending Models - A Caution About Blending Constraints OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 10. To specify that X1 must be at most 75% of the blend of X1, X2, and X3, we must have a constraint of the form a. X1 ≥ 0.75(X2 + X3) b. X1 ≤ 0.25(X1 + X2 + X3) c. X1 ≤ 0.75(X1 + X2 + X3) d. 0.75X1 ≥ X1 + X2 + X3 ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 4.5 Blending Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 11. One way to solve a dual-objective problem is to use one objective as the target cell and constrain the other. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.2 Advertising Models - A Dual Objective Extension of the Model OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models DATE MODIFIED: 10/21/2017 8:44 PM 12. Multiple optimal solutions are quite common in linear programming models. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 13. Integer programming (IP) models are optimization models in which all of the variables must be integers. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.2 Advertising Models - Using Integer Constraints OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 14. If we round the optimal values in the changing cells of a linear programming model, this is a good approximation of the integer programming solution. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.2 Advertising Models - Using Integer Constraints OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 15. If integer constraints are used in a model, Solver uses an algorithm called branch and round to obtain the solution. a. True Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.2 Advertising Models - Using Integer Constraints OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 16. Solver does not offer a sensitivity report for models with integer constraints. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Challenging |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.3 Employee Scheduling Models - Sensitivity Analysis OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 17. In aggregate planning models, the number of workers available influences the possible production levels. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.4 Aggregate Planning Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 18. Aggregate planning models usually relate a beginning value in one period to an ending value from the previous period. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models HAS VARIABLES: False TOPICS: 4.4 Aggregate Planning Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 19. In aggregate planning models, we can model backlogging of demand by allowing a month's inventory to be negative. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.4 Aggregate Planning Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 20. In blending problems, if a quality constraint involves a quotient, then the problem will be nonlinear. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 4.5 Blending Models - A Caution About Blending Constraints OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM Exhibit 4-1 A hospital emergency room requires different numbers of nurses on different days of the week. The number of full-time employees required to be working (i.e. not on call) each day is given in the table below.

Mon 18

Tue 15

Wed 12

Thu 13

Fri 20

Sat 28

Sun 22

Hospital rules require that nurses work four consecutive days, are on call for one day, and then receive two days off. The hospital wants to meet its daily requirements, while minimizing the number of nurses that must be on staff.

21. Refer to Exhibit 4-1. Use Solver to formulate and solve the hospital's problem.

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Chapter 4 - Linear Programming Models ANSWER:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-1 TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 22. Refer to Exhibit 4-1. Suppose the hospital is experiencing a budget crunch and needs to use the nurses' on call day to temporarily staff the emergency room. Use Solver to formulate and solve the hospital's problem.

ANSWER:

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-1 TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 23. Refer to Exhibit 4-1. Suppose the hospital has 40 nurses and is not allowed to hire or fire any employees, and cannot temporarily schedule nurses on their on call days. Determine a schedule that maximizes the number of weekend days off received by the nurses.

ANSWER: Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-1 TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM Exhibit 4-2 A construction company is preparing for a nine-month project, and will need to develop a staffing plan. The company can assign up to 30 of its own full-time employees to the project, and will hire short-term contract employees to make up any shortage in meeting the personnel requirements. Company employees earn $6,000 per month, while short-term contract employees make $8,600/month. Contract employees can be assigned to the project beginning in any month, and their contract period is two months. The number of workers required for the project by month is shown below:

24. Refer to Exhibit 4-2. Determine the optimal staffing plan for the project.

ANSWER:

POINTS: DIFFICULTY:

1 Challenging |Bloom's Application

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Chapter 4 - Linear Programming Models QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-2 TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 25. 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.

ANSWER:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-2 TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 26. 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?

ANSWER: $250,000 − ($3,436,400 − $3,387,200) = $200,800 POINTS: 1 DIFFICULTY: Moderate |Bloom's Evaluation QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-2 TOPICS: 4.3 Employee Scheduling Models OTHER: BUSPROG - Analytic DISC - Linear Programming Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM Exhibit 4-3 A meat market manager for a large grocery store is preparing a processing plan to stock the shelves with sausage, ground meat, and jerky, which he can prepare from beef, pork and venison. Sausage and ground meat can be made of any mix of the beef, pork and venison, as long at the fat contents are below 15% for sausage and 10% for ground meat. Sausage sells for $5/pound and ground meat sells for $3/pound. Jerky, which sells or $10/pound, is made in a drying process from beef or venison. In the drying process, there is a 50% loss in weight for jerky made from beef (e.g., one pound of beef yields 0.5 pounds of beef jerky) and a 20% loss in weight for jerky made from venison. The market can sell at most 500 pounds of sausage, 1000 pounds of ground meat, and 100 pounds of jerky before their expiration dates. There are currently 1,000 pounds of beef (10% fat content), 500 pounds of pork (8% fat content), and 200 pounds of venison (2% fat content) available for processing.

27. Refer to Exhibit 4-3. Determine the optimal processing plan for the meat market.

ANSWER:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-3 TOPICS: 4.5 Blending Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM

28. [Part 1] Refer to Exhibit 4-3. Suppose that later in the year, venison will be out of season, but the market will be able to obtain an additional 300 pounds of pork for the same costs. Develop a processing plan in that case. How does the solution change?

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Chapter 4 - Linear Programming Models ANSWER:

The maximum amounts of each product can still be made. The jerky will be made from beef, instead of venison, and the additional pork will be used in making ground meat, since less beef will be available for that purpose.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-3 TOPICS: 4.5 Blending Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 29. [Part 2] Refer to Exhibit 4-3. What happens to the revenue when the optimal plan changes to the one given in Part 1?

ANSWER: Nothing − it stays at $6,500 because the amount of the three products made stays that same.

POINTS: 1 DIFFICULTY: Easy |Bloom's Evaluation QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-3 TOPICS: 4.5 Blending Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM Exhibit 4-4 A company blends nitrogen and phosphorous to produce two types of fertilizers. Fertilizer 1 must be at least 50% nitrogen and sells for $55 per pound. Fertilizer 2 must be at least 55% phosphorous and sells for $45 per pound. The company can purchase up to 9000 pounds of nitrogen at $20 per pound and up to 12,000 pounds of phosphorous at $12 per pound.

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Chapter 4 - Linear Programming Models 30. Refer to Exhibit 4-4. Assuming that all fertilizer produced can be sold, determine the optimal blending plan for the company. What is the maximum profit?

ANSWER:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 04-4 TOPICS: 4.5 Blending Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM 31. Refer to Exhibit 4-4. Suppose the company could acquire 1,000 pounds more of either nitrogen or phosphorous.

Which should it choose? What would be the resulting impact on profit?

ANSWER:

The shadow price for nitrogen ($45) is higher than that of phosphorous ($33), and 1,000 pounds is within the allowable increase, therefore the company should acquire the extra nitrogen. This would increase profit by $45,000.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Evaluation QUESTION TYPE: Subjective Short Answer Copyright Cengage Learning. Powered by Cognero.

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Chapter 4 - Linear Programming Models HAS VARIABLES: False PREFACE NAME: Exhibit 04-4 TOPICS: 4.5 Blending Models OTHER: BUSPROG - Analytic DISC - Linear Programming DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:44 PM

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Chapter 5 - Network Models 1. Problems which deal with the direct distribution of products from supply locations to demand locations are called: a. transportation problems b. assignment problems c. network problems d. transshipment problems ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.2 Transportation Models OTHER: BUSPROG - Communication DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 2. The objective in transportation problems is typically to: a. maximize profits b. maximize revenue c. minimize costs d. maximize feasibility ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.2 Transportation Models OTHER: BUSPROG - Communication DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 3. 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 ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.2 Transportation Models - Developing the Spreadsheet Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 5 - Network Models 4. The decision variables in transportation problems are: a. profits b. costs c. flows d. capacities ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.2 Transportation Models - Solution OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 5. 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 ANSWER: a POINTS: 1 DIFFICULTY: Moderate |Bloom's Evaluation QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.2 Transportation Models - Sensitivity Analysis OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 6. The network model representation of the transportation problem has the following advantage relative to the special case of a simple transportation model: a. it does not require capacity restrictions on the arcs of the network b. the flows in the network model don't all necessarily have to be from supply locations to demand locations c. a network model representation is generally easier to formulate and solve d. All of these options ANSWER: b POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.2 Transportation Models - An Alternative Model OTHER: BUSPROG - Analytic DISC - Network Models Copyright Cengage Learning. Powered by Cognero.

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Chapter 5 - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 7. In a typical network model representation of the transportation problem, the nodes indicate a. roads b. rail lines c. geographic locations d. rivers ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.2 Transportation Models - An Alternative Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 8. 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 ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.2 Transportation Models - An Alternative Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 9. In an assignment model of machines to jobs, the machines are analogous to which of the following in a transportation problem? a. Suppliers b. Customers c. Flows d. Unit capacities ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension Copyright Cengage Learning. Powered by Cognero.

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Chapter 5 - Network Models QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.3 Assignment Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 10. 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 ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Evaluation QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 5.4 Other Logistics Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 11. The graphical representation of a network in an optimization problem can be an aid in the development of a spreadsheet model. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.1 Introduction OTHER: BUSPROG - Communication DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 12. It is useful to model network problems by listing all of the arcs and their corresponding flows in one long, comprehensive list. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False Copyright Cengage Learning. Powered by Cognero.

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Chapter 5 - Network Models HAS VARIABLES: False TOPICS: 5.2 Transportation Models - An Alternative Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 13. In transportation problems, shipments between supply points or between demand points are possible. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.2 Transportation Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 14. In transportation problems, the three sets of input numbers that are required are capacities, demands and flows. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.2 Transportation Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 15. In network models of transportation problems, arcs represent the routes for getting a product from one node to another. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.2 Transportation Models - An Alternative Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 5 - Network Models DATE MODIFIED: 10/21/2017 8:55 PM 16. In an optimized shipping plan, most of the shipments occur on the low-cost routes, but this is not always the case. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.2 Transportation Models - Discussion of Solution OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 17. Transshipment points are locations where goods neither originate nor end up, but goods are allowed to enter such points to be shipped out to their eventual destinations. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.4 Other Logistics Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 18. The flow balance constraint for each transshipment node in a network flow model has the form Flow in = Flow out. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.5 Shortest Path Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 19. A typical shortest path problem is a special case of the general network flow model. a. True Copyright Cengage Learning. Powered by Cognero.

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Chapter 5 - Network Models b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.5 Shortest Path Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 20. The cost of an arc in a shortest path problem is not necessarily equal to the distance of the arc. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 5.5 Shortest Path Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM Exhibit 5-1 Sinclair Plastics operates two chemical plants which produce polyethylene; the Ohio Valley plant which can produce up to 10,000 tons per month and the Lakeview plant which can produce up to 7,000 tons per month. Sinclair sells its polyethylene to three different auto manufacturing plants, Grand Rapids (demand = 3000 tons per month), Blue Ridge (demand = 5000 tons per month), and Sunset (demand = 4000 tons per month). The costs of shipping between the respective plants is shown in the table below: Ohio Valley Lakeview

Grand Rapids 50 60

Blue Ridge 40 50

Sunset 100 75

21. Refer to Exhibit 5-1. Formulate (write out algebraically) an LP transportation model to help Sinclair minimize its shipping costs.

ANSWER: Let the decision variables (quantities shipped between plants) be: Ohio Valley (1) Lakeview (2)

Maximize Subject to:

Grand Rapids (1)

Blue Ridge (2)

Sunset (3)

x11 x21

x12 x22

x13 x23

50x11 + 40x12 + 100x13 + 60x21 + 50x22 + 75x23 x11 + x12+ x13 ≤ 10000 x21 + x22+ x23 ≤ 7000

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(Ohio Valley supply) (Lakeview supply) Page 7

Chapter 5 - Network Models x11 + x21 ≥ 3000 x12 + x22 ≥ 5000 x13 + x23 ≥ 4000

(Grand Rapids demand) (Blue Ridge demand) (Sunset demand)

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-1 TOPICS: 5.2 Transportation Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 22. Refer to Exhibit 5-1. Implement the LP model in Solver and obtain the optimal shipping plan. What is the optimized cost?

ANSWER: The optimized model below shows the shipping plan, which results in a total cost of $650,000.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-1 TOPICS: 5.2 Transportation Models - Developing the Spreadsheet Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 23. Refer to Exhibit 5-1. Suppose the Lakeview plant was required to run at capacity. How much more would the shipping plan cost Sinclair?

ANSWER: The optimized model below shows the updated shipping plan, which results in a total cost of $680,000, or $30,000 more than the base case.

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Chapter 5 - Network Models

POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-1 TOPICS: 5.2 Transportation Models - Developing the Spreadsheet Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 24. 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?

ANSWER: The optimized model below shows the updated shipping plan, which results in a total cost of $717,500, or $67,500 more than the base case.

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Chapter 5 - Network Models

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-1 TOPICS: 5.2 Transportation Models - Developing the Spreadsheet Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM Exhibit 5-2 A small engineering firm employs one civil engineer, two engineering technicians, and one summer intern. The types of projects the firm does includes surveys (typically 7 per month), designs (5 per month), and construction project plans (four per month). The times, in hours, required for each employee to complete teach type of project are shown below.

Based on their capabilities and time spent on travel and administrative tasks, the engineer, tech 1, tech 2, and intern can handle 5, 4, 4, and 3 projects per month, respectively.

Engineer Technician 1 Technician 2 Intern

Survey 30 25 20 35

Design 35 50 55 45

Plan 30 45 40 55

25. Refer to Exhibit 5-2. Implement a LP model in Solver and determine the optimal monthly assignment plan for the firm. What is the total number of hours that will be assigned to projects each month?

ANSWER: The optimized model below shows the assignment plan, which results in 495 total hours per month.

(Note that there are multiple optimal solutions.)

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Chapter 5 - Network Models

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-2 TOPICS: 5.3 Assignment Models - Developing the Spreadsheet Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 26. Refer to Exhibit 5-2. Suppose Tech 2 will not be available during the next month. Keeping the same number of design and construction plan projects, how many survey projects would the firm be able to do? What would be the revised assignment plan in that case?

ANSWER: The number of survey jobs must be reduced to three in order for Solver to find a feasible solution.

The optimized model below shows the revised assignment plan, which results in 415 total hours for the month.

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Chapter 5 - Network Models

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-2 TOPICS: 5.3 Assignment Models - Developing the Spreadsheet Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 27. Refer to Exhibit 5-2. Based on their salaries, the engineer, tech 1, tech 2, and intern earn $90, $65, $65, and $45 per hourly, respectively. Change the firm's objective function to minimize staff costs and find the optimal assignment plan.

Does it change from the base case?

ANSWER: The assignment plan may change slightly. The engineer drops one design project and takes on one more planning project, with Tech 1 picking up the dropped design project.

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Chapter 5 - Network Models

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-2 TOPICS: 5.3 Assignment Models - Developing the Spreadsheet Model OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM Exhibit 5-3 Steve the auto parts salesman is trying to navigate his way between the rural west Texas towns of Jonestown and Upland.

The possible routes for this trip are shown below, along with the mileage along each route.

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Chapter 5 - Network Models

28. Refer to Exhibit 5-3. What general type of LP model can be applied to this problem? What modifications to the general type are required for this problem?

ANSWER: The problem can be formulated as a general logistics model which minimizes the cost of network flow. There are no arc capacities required for this type of problem (shortest path problem).

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-3 TOPICS: 5.5 Shortest Path Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 29. 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?

ANSWER: The optimized shortest path model is shown below. Steve will travel 110 miles, through Haleyville, Krickburg, and Baker.

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Chapter 5 - Network Models

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-3 TOPICS: 5.5 Shortest Path Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM 30. 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?

ANSWER: The revised shortest path (in minutes) is shown below. Steve will now travel 115 miles (i.e., 115 minutes @ 60 miles per hour) and Krickburg is no longer on his route.

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Chapter 5 - Network Models

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 05-3 TOPICS: 5.5 Shortest Path Models OTHER: BUSPROG - Analytic DISC - Network Models DATE CREATED: 5/17/2017 3:48 PM DATE MODIFIED: 10/21/2017 8:55 PM

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Chapter 6 - Optimization Models with Integer Variables 1. 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 ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.1 Introduction OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 2. In a linear model, the target cell and constraints are ultimately: a. a product of changing cells b. a sum of products of changing cells c. a product of constants and changing cells d. a sum of products of constants and changing cells ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.1 Introduction OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 3. 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 ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.1 Introduction OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables DATE MODIFIED: 10/21/2017 9:05 PM 4. 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 ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.1 Introduction OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 5. The branching part of the branch and bound algorithm that Solver uses to solve integer programming models means that the algorithm: a. creates subsets of solutions through which to search b. searches through only a limited set of feasible integer solutions c. identifies an incumbent solution which is optimal d. uses a decision tree to find the optimal solution ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - Branch and Bound Algorithm OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 6. An algorithm which uses implicit enumeration: a. is impractical b. examines all possible solutions c. does not guarantee that some of the solutions not examined could be optimal d. excludes many possible solutions that guaranteed to be suboptimal ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - Branch and Bound Algorithm Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 7. The branch and bound algorithm uses: a. lower bounds b. upper bounds c. both upper and lower bounds d. neither upper or lower bounds ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - Branch and Bound Algorithm OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 8. The default integer optimality setting in Solver is: a. 0.1% b. 0.5% c. 1% d. 5% ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - The Solver Integer Optimality Setting OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 9. Any integer program involving 0 − 1 variables with ____ constraint(s) is called a knapsack problem. a. three b. two c. one d. zero ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge QUESTION TYPE: Multiple Choice HAS VARIABLES: False Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables TOPICS: 6.3 Capital Budgeting Models - Modeling Issues OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 10. 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 ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 6.4 Fixed-Cost Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 11. Optimization software, including Solver, typically has more difficulty solving an integer programming problem, relative to a linear programming problem. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.1 Introduction OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 12. Solver may be unable to solve some integer programming problems, even when they have an optimal solution. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.1 Introduction OTHER: BUSPROG - Analytic |DISC - Integer Models Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 13. Complete enumeration of all possible solutions in many integer programming problems is impractical. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - Branch and Bound Algorithm OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 14. During the solution of a maximization problem with the branch and bound algorithm, an incumbent solution represents an upper bound on the solution. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - Branch and Bound Algorithm OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 15. The higher the upper bound produced for a maximization problem in the branch and bound solution process, the faster the algorithm will be. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - Branch and Bound Algorithm OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 16. If Solver fails to find an optimal solution to an integer programming problem, we might be able to find a near optimal Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables solution by specifying a smaller number for the integer optimality setting. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - The Solver Integer Optimality Setting OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 17. 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 ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.2 Overview of Optimization with Integer Variables - The Solver Integer Optimality Setting OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 18. Problems with a fixed cost that is incurred only if an activity is undertaken at a positive level are inherently nonlinear. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.4 Fixed-Cost Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 19. Fixed costs imply that the divisibility assumption of linear models no longer holds. a. True b. False ANSWER: False Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.4 Fixed-Cost Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 20. In a set-covering model, each member of a given set (set 1) must be "covered" by all members of another set (set 2). a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 6.5 Set-Covering and Location-Assignment Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM Exhibit 6-1 A recent college graduate is planning to move cross country from her college town to the city where her first job is located. She has rented a truck that can haul up to 1100 cubic feet of furniture. The volume and value of each item she is considering moving on the truck are given below.

21. Refer to Exhibit 6-1. This problem is an example of what type of integer programming model?

ANSWER: This is an integer programming model requiring binary variables (to indicate which items the graduate will move) and a single constraint (the capacity of the moving truck), therefore it is a knapsack problem.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 06-1 TOPICS: 6.3 Capital Budgeting Models - Modeling Issues OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables 22. Refer to Exhibit 6-1. Which items should she take with her to her new home? What is the value of these items?

ANSWER: The solved knapsack model is shown below. She should take the dining set, soft and TV, which have a combined total value of $800.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 06-1 TOPICS: 6.3 Capital Budgeting Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 23. Refer to Exhibit 6-1. Suppose she can save $400 by renting a smaller truck, which has only 800 cubic feed of capacity.

Would she be better off with the smaller truck?

ANSWER: The revised knapsack model is shown below. In this case, she would take only the dining set and the TV, which have a combined total value of $600. This is $200 less value than before, but she would save twice that with the smaller truck.

POINTS:

1

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Chapter 6 - Optimization Models with Integer Variables DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 06-1 TOPICS: 6.3 Capital Budgeting Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM Exhibit 6-2 Sinclair Plastics operates two chemical plants which produce polyethylene; the Ohio Valley plant which can produce up to 10,000 tons per month and the Lakeview plant which can produce up to 7,000 tons per month. Sinclair sells its polyethylene to three different auto manufacturing plants, Grand Rapids (demand = 3000 tons per month), Blue Ridge (demand = 5000 tons per month), and Sunset (demand = 4000 tons per month). The variable unit cost of shipping a ton is $1 per mile. The number of miles between the respective plants is shown in the table below: Ohio Valley Lakeview

Grand Rapids 50 60

Blue Ridge 40 50

Sunset 100 75

In addition to the variable unit costs of shipping, Sinclair incurs a fixed handling cost (of pickup and delivery) for any shipping routes it uses. These costs are discounted for longer routes, as shown below:

24. Refer to Exhibit 6-2. This problem is an example of what type of integer programming model?

ANSWER: This problem requires an integer programming model with binary variables to indicate when the fixed costs are incurred, therefore it is a fixed cost problem.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 06-2 TOPICS: 6.4 Fixed-Cost Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 25. Refer to Exhibit 6-2. What problem will occur if we use an IF statement to model the fixed handling costs?

ANSWER: The success of a model using IF statements will depend on the starting values used, and may not always provide the optimal solution.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 06-2 TOPICS: 6.4 Fixed-Cost Models - A Model with IF Functions OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 26. Refer to Exhibit 6-2. What is Sinclair's optimal shipping plan? What is the total cost in that case?

ANSWER: The solved model is shown below. Sinclair will ship from Ohio Valley to Blue Ridge, and from Lakeview to Grand Rapids and Sunset. The total cost is $780,000.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 06-2 TOPICS: 6.4 Fixed-Cost Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 27. 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?

ANSWER: The solved model is shown below. Sinclair will be forced to use all but the Lakeview to Grand Rapids route, which increases the total cost substantially to $895,000.

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Chapter 6 - Optimization Models with Integer Variables

POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 06-2 TOPICS: 6.4 Fixed-Cost Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM Exhibit 6-3 PharmaCo wants to determine how to deploy sales representatives across its Western U.S. region to support a new drug for obesity. Sales representatives will be located in a "home city", which they serve, in addition to cities with feasible commuting distance, with the objective that all cities must be served by at least one sales representative. The feasible connections between each city in the region are listed below (1 indicates a feasible connection):

28. Refer to Exhibit 6-3. This problem is an example of what type of integer programming model?

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Chapter 6 - Optimization Models with Integer Variables ANSWER:

This problem requires that every member of a given set (the cities) to be covered by an acceptable (within commuting distance) member of another set (the sales representative home cities), so this is a set covering model.

POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 06-3 TOPICS: 6.5 Set-Covering and Location-Assignment Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:05 PM 29. Refer to Exhibit 6-3. Formulate an integer programming model to identify a feasible deployment plan to the sales representatives. What is the minimum number of representatives that can cover this region? What are their home cities?

ANSWER: PharmaCo will need to deploy 2 sales representatives. One feasible solution is for their home cities to be Phoenix and Seattle.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYP Subjective Short Answer E: HAS VARIABLE False S: PREFACE NAM Exhibit 06-3 E: TOPICS: 6.5 Set-Covering and Location-Assignment Models OTHER: BUSPROG - Analytic |DISC - Integer Models Copyright Cengage Learning. Powered by Cognero.

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Chapter 6 - Optimization Models with Integer Variables DATE CREATE 5/17/2017 3:49 PM D: DATE MODIFIE 10/21/2017 9:05 PM D: 30. 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?

ANSWER: PharmaCo would need to deploy 3 additional sales representatives (five total). One feasible solution is for their home cities to be in Albuquerque, San Diego, Los Angeles, Seattle and Las Vegas.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYP Subjective Short Answer E: HAS VARIABLE False S: PREFACE NAM Exhibit 06-3 E: TOPICS: 6.5 Set-Covering and Location-Assignment Models OTHER: BUSPROG - Analytic |DISC - Integer Models DATE CREATE 5/17/2017 3:49 PM D: DATE MODIFI 10/21/2017 9:05 PM ED:

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Chapter 7 - Nonlinear Optimization Models 1. Which of the following is not one of the reasons an optimization model can become nonlinear? a. Nonconstant returns to scale. b. The model objective is to minimize the sum of squared differences. c. The model objective is a function of a variable times multiplied by a function of that same variable d. The model objective is to minimize the sum of absolute errors.

ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.1 Introduction OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 2. Which of the following is not one of the common types of nonlinear models? a. Pricing models. b. Advertising and response selection models. c. Network flow models. d. Portfolio optimization models.

ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.1 Introduction OTHER: BUSPROG - Communication |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 3. 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 ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - Convex and Concave Functions OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 7 - Nonlinear Optimization Models 4. If a convex function is multiplied by a negative constant, the result: a. is convex b. is concave c. could be either convex or concave, depending on the value of the constant d. is linear ANSWER: b POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - Convex and Concave Functions OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 5. Which of the following is not one of the conditions for maximization in a nonlinear problem? a. The objective function is concave b. The logarithm of the objective function is concave c. The starting values are bounded d. The constraints are linear ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - Conditions for Maximization Problems OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 6. 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 ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - When the Assumptions Do Not Hold OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 7 - Nonlinear Optimization Models DATE MODIFIED: 10/21/2017 9:14 PM 7. 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 ANSWER: b POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - Multistart Option OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 8. In pricing models, elasticity of demand is an input with specifies the: a. range of demand b. level of demand c. sensitivity of price to changes in demand d. sensitivity of demand to changes in price ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.3 Pricing Model OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 9. Which of the following types of fit should be selected in Excel's Trendline function if a constant elasticity curve is to be used to model demand? a. Exponential b. Logarithmic c. Polynomial d. Power ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.3 Pricing Model - Estimating the Demand Function Copyright Cengage Learning. Powered by Cognero.

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Chapter 7 - Nonlinear Optimization Models OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 10. 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 ANSWER: a POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 7.4 Advertising Response and Selection Models - Developing the Spreadsheet Model OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 11. Relative to linear optimization models, nonlinear optimization models are typically more difficult to solve. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.1 Introduction OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 12. Solver can get stuck at a global optimum and never find the local optimum. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 7 - Nonlinear Optimization Models 13. Solver is guaranteed to solve certain types of nonlinear programming models. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - Problems That Solvers Always Solve Correctly OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 14. A function is convex if a line drawn connecting two points on the curve never lies below the curve. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - Convex and Concave Functions OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 15. The sum of two concave functions is concave. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - Convex and Concave Functions OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 16. 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 Copyright Cengage Learning. Powered by Cognero.

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Chapter 7 - Nonlinear Optimization Models ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.2 Basic Ideas of Nonlinear Optimization - Conditions for Minimization Problems OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 17. In pricing models, two products are substitutes for each other if a larger price for one product tends to induce customers to demand less of the other. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.3 Pricing Model - Electricity Pricing at Florida Power and Light OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 18. 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 ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.4 Advertising Response and Selection Models OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 19. In some nonlinear models, Solver will find the optimal solution only if the starting solution is reasonably close to the optimal solution. a. True b. False ANSWER: True POINTS: 1 Copyright Cengage Learning. Powered by Cognero.

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Chapter 7 - Nonlinear Optimization Models DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.4 Advertising Response and Selection Models - Is the Solver Solution Optimal?

OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 20. The amount invested is one of the required inputs in a portfolio optimization model. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 7.7 Portfolio Optimization Models - Solution OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM Exhibit 7-1 A company manufactures two products. If it charges price p1 for product 1 and price p2 for product 2, it can sell quantities q1 = 55 − 3p1 + 2p2 and q2 = 75 + 2p1 − 2p2 for products 1 and 2, respectively. It costs the company $20 to produce a unit of product 1 and $65 to produce a unit of product 2.

21. Refer to Exhibit 7-1. How many units of each product should the company produce? What prices should it charge, to maximize profit?

ANSWER: The optimized model below shows that the company should produce 55 units of product 1 and no units of product 2, which will generate total profit of $3,025. The respective prices of product 1 and product 2 are $75 and $112.50.

POINTS: DIFFICULTY: QUESTION TYPE: HAS VARIABLES:

1 Moderate |Bloom's Application Subjective Short Answer False

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Chapter 7 - Nonlinear Optimization Models PREFACE NAME: Exhibit 07-1 TOPICS: 7.3 Pricing Model OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 22. Refer to Exhibit 7-1. Suppose the company must produce a minimum of 20 units of each product. How many units of each product should the company produce in that case? What prices should it charge, to maximize profit?

ANSWER: The optimized model with an added production constraint shows that the company should produce 35 units of product 1 and the minimum of 20 units of product 2, which reduces total profit to $2,675.

The respective prices of product 1 and product 2 are $75 and $102.50.

POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 07-1 TOPICS: 7.3 Pricing Model OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 23. 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?

ANSWER: The optimized model with the added constraint below shows that the company should produce 18 units of product 1 and no units of product 2, which reduces total profit to only $306. The price of both products is $37.00. Note that integer constraints were imposed on the production quantities.

POINTS: DIFFICULTY: QUESTION TYPE: HAS VARIABLES: PREFACE NAME: TOPICS:

1 Easy |Bloom's Application Subjective Short Answer False Exhibit 07-1 7.3 Pricing Model

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Chapter 7 - Nonlinear Optimization Models OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM Exhibit 7-2 A soda producer makes and sells two products, Classic Cola and Diet Cola. During the planning period, if the producer spends x1 dollars on promotion of Classic Cola, it can sell 100x10.5 cases of Classic Cola, and if it spends x2 dollars on promotion of Diet Cola, it can sell 10x20.75 cases of Diet Cola. Each case of Classic Cola sells for $12.00 and costs $0.95 to produce and ship to customers, while each case of Diet Cola sells for $12.50 and costs $1.00 to produce and ship to customers. A total of $7,500 is available for promotion during the planning period.

24. Refer to Exhibit 7-2. Formulate and solve a nonlinear optimization model to help this soda producer identify the best promotional strategies for its two products.

ANSWER: The optimized model below shows that the company should spend $2,810 promoting Classic Cola and $4,690 promoting Diet Cola, which will generate total profit of $116,250.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 07-2 TOPICS: 7.4 Advertising Response and Selection Models OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 25. Refer to Exhibit 7-2. Suppose the producer can double the promotional budget. Formulate and solve a nonlinear optimization model to help this soda producer identify the best promotional strategies for its two products in that case.

Does the change in profit justify the budget increase? Does the proportional amount spent promoting the two products remain the same?

ANSWER: The optimized model below shows that the company should spend $4,254 promoting Classic Cola and $10,746 promoting Diet Cola, which will generate total profit of $178,447. Therefore, the increase in budget is well worth it. The proportional amount spent promoting Diet Cola grows from 62.5% in the $7,500 budget case to 71.6% in this case.

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Chapter 7 - Nonlinear Optimization Models

POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 07-2 TOPICS: 7.4 Advertising Response and Selection Models OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM Exhibit 7-3 A company has the following historical data on the number of ad exposures and the corresponding number of units sold of one of its products:

26. [Part 1] Refer to Exhibit 7-3. Formulate a nonlinear optimization model to find the parameters of a function of the form: f(x) = axb to model demand for its product as a function of ad exposures (x).

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Chapter 7 - Nonlinear Optimization Models ANSWER:

The parameterized model is:

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 07-3 TOPICS: 7.4 Advertising Response and Selection Models - Estimating Advertising Response Function OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 27. [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 ANSWER: The parameterized model is:

The sum of squared errors is lower (48.7 vs. 689.9) in this case, so this is a better model.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 07-3 TOPICS: 7.4 Advertising Response and Selection Models - Estimating Advertising Response Function OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM Exhibit 7-4 You are given the following means, standard deviations, and correlations for the annual return on three stocks. The means are 0.08, 0.10, and 0.15. The standard deviations are 0.15, 0.20, and 0.30. The correlation between stocks 1 and 2 is 0.62, between stocks 1 and 3 is 0.32, and between stocks 2 and 3 is 0.43.

28. [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 7 - Nonlinear Optimization Models ANSWER:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 07-4 TOPICS: 7.7 Portfolio Optimization Models OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 29. [Part 2] Refer to Exhibit 7-4. Determine the minimum variance portfolio that yields an expected annual return of at least 0.12. How has the portfolio changed from your answer in Part 1?

ANSWER: The optimized portfolio is heavily weighted to Stock 3, which increases the standard deviation by 50%.

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Chapter 7 - Nonlinear Optimization Models

POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 07-4 TOPICS: 7.7 Portfolio Optimization Models OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM 30. Refer to Exhibit 7-4. Suppose you set the weights in the portfolio to a maximum of 0.45 for each stock. Is it possible to achieve a 12% return? What is the portfolio standard deviation in that case?

ANSWER: Yes, the optimized portfolio with the added diversification constraint shows that a 12% return is still achievable. The standard deviation of the return increases slightly to .198.

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Chapter 7 - Nonlinear Optimization Models

POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 07-4 TOPICS: 7.7 Portfolio Optimization Models OTHER: BUSPROG - Analytic |DISC - Nonlinear Models DATE CREATED: 5/17/2017 3:49 PM DATE MODIFIED: 10/21/2017 9:14 PM

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure 1. Evolutionary Solver is primarily used to solve models where: a. some or all of the changing cells are restricted to be binary and/or integer b. the objective cell and constraints are "smooth" functions of the changing cells c. there are numerous constraints d. the objective call and constraints are "nonsmooth" functions of the changing cells ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.1 Introduction OTHER: BUSPROG - Communication |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 2. Which of the following is not one of the Excel functions that necessitate the use of Evolutionary Solver to obtain solutions? a. SUM b. IF c. MAX d. MIN ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.1 Introduction OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 3. The objective function in a genetic algorithm is called a: a. chromosome b. fitness function c. population d. generation ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.2 Introduction to Genetic Algorithms OTHER: BUSPROG - Communication |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure DATE MODIFIED: 10/21/2017 9:29 PM 4. Which of the following is not a step in a genetic algorithm? a. Generating a population b. Creating a new generation c. Culling the population d. Evaluating a stopping condition ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.2 Introduction to Genetic Algorithms OTHER: BUSPROG - Communication |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 5. 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 ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.3 Introduction to Evolutionary Solver OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 6. The Evolutionary Solver setting that helps the algorithm explore a completely different area of the feasible region is: a. convergence b. mutation rate c. population size d. random seed ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.3 Introduction to Evolutionary Solver OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 7. Which of the following is not a form of non-linear pricing? a. Two-part tariff b. Surplus value c. Selling only single item packs or packs of n items d. Charging one price for the first n items and another price for the rest ANSWER: b POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.4 Nonlinear Pricing Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 8. Evolutionary Solver works best when constraints are applied as: a. penalties b. shortages c. capacities d. targets ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.3 Introduction to Evolutionary Solver OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 9. For which of the following problems is the alldifferent constraint particularly useful? a. nonlinear pricing b. shortest path c. estimating an S shaped relationship d. portfolio optimization ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.8 Optimal Permutation Models Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 10. The number of possible paths in a shortest path problem with n locations is: a. n b. n − 1 c. n2 d. n!

ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 8.8 Optimal Permutation Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 11. The initial set of chromosomes generated by a genetic algorithm is called the population. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.2 Introduction to Genetic Algorithms OTHER: BUSPROG - Communication |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 12. Crossovers are rare as a genetic algorithm is generating chromosomes for the next generations. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.2 Introduction to Genetic Algorithms OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure 13. Mutations are useful for getting a genetic algorithm "unstuck". a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.2 Introduction to Genetic Algorithms OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 14. If you let a genetic algorithm run long enough, it is guaranteed to find the solution to any optimization problem. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.2 Introduction to Genetic Algorithms OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 15. In Evolutionary Solver, the initial population is chosen randomly, so the starting solution you enter in the changing cells is irrelevant. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.3 Introduction to Evolutionary Solver OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 16. Combinatorial problems have only a finite number of feasible solutions. a. True b. False Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.5 Combinatorial Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 17. Genetic algorithms are not guaranteed to be fast, but they make up for it by being flexible. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.3 Introduction to Evolutionary Solver OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 18. 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 ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.2 Introduction to Genetic Algorithms OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 19. With two-part tariff pricing, it is assumed that a customer buys the quantity that provides the largest difference between value and total price. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Application Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.4 Nonlinear Pricing Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 20. 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 ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 8.8 Optimal Permutation Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM Exhibit 8-1 Six storage bins on a railroad train are available for shipment of grain from Kansas City to Dallas. Three of the bins can hold 1500 bushels of grain each, while the other three can hold 750 bushels each. There are four types of grain that can be shipped, and the amount demanded, unit shortage cost and maximum allowable shortage for each are:

If the maximum allowable shortage is exceeded for any grain, a $100/bushel penalty is incurred.

21. Refer to Exhibit 8-1. This is an example of what type of optimization problem?

ANSWER: The decision maker must find the best of many different possible combinations (i.e., different types of grain stored in different bins), so it is a combinatorial optimization problem.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 08-1 TOPICS: 8.5 Combinatorial Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure 22. Refer to Exhibit 8-1. How should the train be loaded to minimize shortage and penalty costs?

ANSWER: The solution obtained with Evolutionary Solver is shown below:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE Subjective Short Answer : HAS VARIABLES: False PREFACE NAME Exhibit 08-1 : TOPICS: 8.5 Combinatorial Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIE 10/21/2017 9:29 PM D: Exhibit 8-2 A television station has commercials of the following lengths (in seconds): 15, 20, 25, 30, 40, 45, 50, and 60. The commercials must be assigned to 90-second breaks. If a commercial break exceeds 90 seconds, a penalty cost is incurred.

Station managers have established a penalty of $100 (per second) if the maximum limit is exceeded. Moreover, station owners want commercial breaks that are at least 65 seconds in duration. If any break fails to achieve this minimum duration, then a $1000 penalty (per occurrence) is charged.

23. Refer to Exhibit 8-2. What is the fewest number of breaks that are needed to air all eight of the commercials?

ANSWER: The solution obtained with Evolutionary Solver is shown below. A minimum of three breaks is required to air all eight commercials.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 08-2 TOPICS: 8.5 Combinatorial Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 24. Refer to Exhibit 8-2. Explain why this problem typically requires Evolutionary Solver to obtain a solution.

ANSWER: There are different ways to formulate this problem, but all formulations are likely to use the SUMIF, IF, and MAX or MIN functions. Evolutionary Solver is able to handle the nonlinear and non-smooth conditions resulting from the use of these functions.

POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 08-2 TOPICS: 8.5 Combinatorial Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM Exhibit 8-3 A gourmet snack company is seeking assistance with its pricing strategy. Information about market size and customer Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure sensitivity to price for the three market segments are provided below.

25. Refer to Exhibit 8-3. Given that the unit cost of the gourmet snack is $2.50, use a single price model and evolutionary solver to determine the best unit price for them to charge.

ANSWER: Using Evolutionary Solver, the price should be $3.30.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 08-3 TOPICS: 8.4 Nonlinear Pricing Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 26. 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.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure ANSWER:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 08-3 TOPICS: 8.4 Nonlinear Pricing Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM 27. Refer to Exhibit 8-3. Due to a social media frenzy, the third customer segment now attaches more value to this gourmet snack. All of the prices it is willing to pay have increased by 20%. How does this change the recommended pricing strategy?

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure ANSWER:

The fixed price has increased from $1.85 to $3.23.

The unit price has increased from $2.60 to $2.76.

The profit has increase from $842.47 to $1,230.86.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 08-3 TOPICS: 8.4 Nonlinear Pricing Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:29 PM Exhibit 8-4 Steve the salesman must travel along a route from his home in Denver that visits all of the cities shown below exactly once before returning home. The mileage between each city on the route is also listed below:

28. 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?

ANSWER: The shortest path and total distance are shown below: Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 08-4 TOPICS: 8.8 Optimal Permutation Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED 10/21/2017 9:29 PM : 29. Refer to Exhibit 8-4. Suppose Steve moves to Los Angeles. What is the shortest distance in this case?

ANSWER: The shortest path is shown below. The total distance is the same (it does not matter from which city Steve begins his route).

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE Subjective Short Answer : HAS VARIABLES False : PREFACE NAME Exhibit 08-4 : TOPICS: 8.8 Optimal Permutation Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED 5/17/2017 3:50 PM : Copyright Cengage Learning. Powered by Cognero.

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Chapter 8 - Evolutionary Solver: An Alternative Optimization Procedure DATE MODIFIE 10/21/2017 9:29 PM D: 30. Refer to Exhibit 8-4. Suppose Steve's company decides to locate a second salesperson in the region. Steve will now cover only Denver, Albuquerque, El Paso, Phoenix and Salt Lake City. The second salesperson will cover Los Angeles, San Diego, San Francisco, Portland, Seattle and Las Vegas. Formulate and solve shortest-path models for both salespersons. Is the total mileage for both salespersons more or less than in the case where Steve is the only salesperson?

ANSWER: The shortest paths are shown below. The distance is more in this case (the extra distance is because both salespersons need to return home at the end of their routes).

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 08-4 TOPICS: 8.8 Optimal Permutation Models OTHER: BUSPROG - Analytic |DISC - Evolutionary Solver DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED 10/21/2017 9:29 PM :

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Chapter 9 - Decision Making Under Uncertainty 1. All problems related to decision making under uncertainty have three common elements: a. the mean, median, and mode b. the set of decisions, the cost of each decision and the profit that can be made from each decision c. the set of possible outcomes, the set of decision variables and the constraints d. the set of decisions, the set of possible outcomes, and a value model that prescribes results ANSWER: d POINTS: 1 DIFFICULTY: Easy | Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.2 Elements of Decision Analysis OTHER: BUSPROG - Communication |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 2. Expected monetary value (EMV) is: a. the average or expected value of the decision if you knew what would happen ahead of time b. the weighted average of possible monetary values, weighted by their probabilities c. the average or expected value of the information if it was completely accurate d. the amount that you would lose by not picking the best alternative ANSWER: b POINTS: 1 DIFFICULTY: Easy | Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.2 Elements of Decision Analysis - Decision Criterion OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 3. Probabilities on the branches of a chance node may be ____ events that have occurred earlier in the decision tree. a. marginal due to b. conditional on c. averaged with d. increased by ANSWER: b POINTS: 1 DIFFICULTY: Moderate | Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 9 - Decision Making Under Uncertainty 4. Which of the following statements is true concerning decision tree conventions? a. Time proceeds from right to left. b. The trees are composed of circles, triangles and ovals. c. The nodes represent points in time. d. Probabilities of outcomes are shown to the right of the end nodes.

ANSWER: c POINTS: 1 DIFFICULTY: Moderate | Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 5. The solution procedure for solving decision trees is called: a. sensitivity analysis b. policy iteration c. risk profiling d. folding back ANSWER: d POINTS: 1 DIFFICULTY: Easy | Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 6. 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 ANSWER: a POINTS: 1 DIFFICULTY: Moderate | Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems - Sensitivity Analysis OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 9 - Decision Making Under Uncertainty DATE MODIFIED: 10/21/2017 9:37 PM 7. 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.

ANSWER: d POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems - Bayes' Rule: Probability Approach OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 8. 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.

ANSWER: b POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems - Bayes' Rule: Probability Approach OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 9. 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 ANSWER: b POINTS: 1 DIFFICULTY: Easy | Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems - Bayes' Rule: Frequency Approach OTHER: BUSPROG - Analytic |DISC - Decision Making Copyright Cengage Learning. Powered by Cognero.

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Chapter 9 - Decision Making Under Uncertainty DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 10. A utility function for risk averse individuals is ____ and/or ____. a. decreasing, linear b. decreasing, convex c. increasing, linear d. increasing, concave ANSWER: d POINTS: 1 DIFFICULTY: Moderate | Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 9.6 The Role of Risk Aversion OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 11. In general, the expected monetary value (EMV) of a decision will be equal to one of the possible payoffs. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy | Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.2 Elements of Decision Analysis - More about the EMV Criterion OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 12. For each possible decision and each possible outcome, the payoff table lists the associated monetary value. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy | Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.2 Elements of Decision Analysis - More about the EMV Criterion OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 9 - Decision Making Under Uncertainty 13. The expected monetary value (EMV) criterion represents the long-run average of uncertain outcomes, so it should only be used for recurring decisions. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate | Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.2 Elements of Decision Analysis - More about the EMV Criterion OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 14. The risk profile from Precision Tree shows the probability distribution of monetary outcomes in both graphical and tabular form. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy | Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems -Solution OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 15. The expected value of information (EVI) is the difference between the EMV obtained with free sample information and the EMV obtained without any information. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate | Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems -The Value of Information OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 16. The expected value of perfect information (EVPI) is a largely irrelevant concept since perfect information is almost never available at any price. a. True Copyright Cengage Learning. Powered by Cognero.

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Chapter 9 - Decision Making Under Uncertainty b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy | Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems -The Value of Information OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 17. Bayes' rule is used for updating the probability of an uncertain outcome after observing the results of a test or study. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy | Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems - Bayes' Rule: Probability Approach OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 18. Prior probabilities are sometimes called likelihoods, the probabilities that are influenced by information about the outcome of an earlier uncertainty. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.5 Multistage Decision Problems - Bayes' Rule: Probability Approach OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 19. The certainty equivalent is the certain dollar amount a risk-averse decision maker would accept in order to avoid a gamble altogether. a. True b. False ANSWER: True POINTS: 1 Copyright Cengage Learning. Powered by Cognero.

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Chapter 9 - Decision Making Under Uncertainty DIFFICULTY: Easy | Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.6 The Role of Risk Aversion OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 20. For a risk averse decision maker, the certainty equivalent is less than the expected monetary value (EMV). a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy | Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 9.6 The Role of Risk Aversion OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM Exhibit 9-1 A farmer must decide whether to take protective action to limit damage to his grapefruit crop in the event that the overnight temperature falls to a level well below freezing. If the temperature drops too low he runs the risk of losing his entire crop, valued at $75,000. Based on the National Weather Service, the probability of such a temperature drop is 60%.

He can insulate his crop by spraying water on all the trees, which will cost $20,000. This action might succeed in protecting the crop, with the following possible outcomes: Probability 0.30 0.15 0.10 0.15 0.30

Damage $0 $5,000 $10,000 $15,000 $20,000

21. Refer to Exhibit 9-1. Construct a decision tree to help the farmer make his decision. What should he do? Explain your answer.

ANSWER: The solved decision tree below shows that it is optimal for the farmer to insulate, since the expected cost is $26,000 if he insulates, versus $45,000 if he doesn't insulate.

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Chapter 9 - Decision Making Under Uncertainty

POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-1 TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 22. Refer to Exhibit 9-1. Find the highest cost of insulating the grapefruits for which the farmer prefers to insulate his crop.

ANSWER: By trial and error (or by looking at the difference in expected values) the decision would switch to "No" (don't insulate) if the cost exceeds $39,000.

POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-1 TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 23. Refer to Exhibit 9-1. Suppose the farmer is uncertain about the reliability of the National Weather Service forecast. If he thinks the probability of a freeze occurring could be anywhere between 40% and 80%, would that change his decision?

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Chapter 9 - Decision Making Under Uncertainty ANSWER:

No, the strategy region chart below shows the best option is to insulate over this entire range of probability.

POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-1 TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM

24. Refer to Exhibit 9-1. Construct a risk profile and from that determine the probability that no additional cost is incurred if the decision to insulate at a cost of $20,000 is made.

ANSWER:

The risk profile is shown below. The probability of incurring no additional cost once the decision to insulate is made is 58%.

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Chapter 9 - Decision Making Under Uncertainty

POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-1 TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 25. Refer to Exhibit 9-1. Suppose the farmer is not risk-neutral, but instead his behavior can be modeled using an exponential utility function with a risk tolerance parameter of 100,000. What is the most he would be willing to pay for insulation in that case?

ANSWER: The risk averse decision tree below shows he would be willing to pay more (˜$45,000).

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Chapter 9 - Decision Making Under Uncertainty

POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-1 TOPICS: 9.6 The Role of Risk Aversion - Exponential Utility OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM Exhibit 9-2 A customer has approached a local credit union for a $20,000 1-year loan at a 10% interest rate. If the credit union does not approve the loan application, the $20,000 will be invested in bonds that earn a 6% annual return. Without additional information, the credit union believes that there is a 5% chance that this customer will default on the loan, assuming that the loan is approved. If the customer defaults on the loan, the credit union will lose the $20,000.

26. 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.

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Chapter 9 - Decision Making Under Uncertainty ANSWER:

POINTS: 1 DIFFICULTY: Moderate | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-2 TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM

27. Refer to Exhibit 9-2. What should the credit union do? What is their expected profit?

ANSWER: The tree shows that the best alternative is not to make the loan, and to invest the funds in bonds earning 6% interest instead. The EMV of this option is $1,200.

POINTS: 1 DIFFICULTY: Easy | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-2 TOPICS: 9.2 Elements of Decision Analysis - Decision Trees OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM 28. Refer to Exhibit 9-2. The bank can thoroughly investigate the customer's credit record and obtain a favorable or unfavorable recommendation. If the credit report is perfectly reliable, what is the most the credit union should be willing to pay for the report?

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Chapter 9 - Decision Making Under Uncertainty ANSWER:

The tree above shows that if the credit report is favorable, the credit union should make the loan, and if the report is unfavorable, it should not make the loan. This increases the expected value to $1,960 with the credit information. Thus, the EVPI is $1960-$1200 = $760, which is the most the credit union should be willing to pay.

POINTS: 1 DIFFICULTY: Challenging | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-2 TOPICS: 9.5 Multistage Decision Problems -The Value of Information OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM

29. Refer to Exhibit 9-2. Should the credit union purchase the report if it costs $150?

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Chapter 9 - Decision Making Under Uncertainty ANSWER:

The tree above shows that the credit report is still valuable, even in the imperfect case. The information increases the expected value to $1,543, thus, the EVSI is $343 ($1,543 − $1,200).

Therefore, the credit union would be justified in purchasing the report for $150.

POINTS: 1 DIFFICULTY: Challenging | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-2 TOPICS: 9.5 Multistage Decision Problems -The Value of Information OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM

30. Refer to Exhibit 9-2. Suppose that an actual (not perfectly reliable) credit report has the following characteristics based on historical data; in cases where the customer did not default on the approved loan, the probability of receiving a favorable recommendation on the basis of the credit investigation was 80%, while in cases where the customer defaulted on the approved loan, the probability of receiving a favorable recommendation on the basis of the credit investigation was 25%. Given this information, what are the posterior probabilities that default will and will not occur, given the credit report?

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Chapter 9 - Decision Making Under Uncertainty ANSWER:

The worksheet above shows that if the report predicts default, the probabilities of actual default and no default are 0.165 and 0.835, respectively, while if the report predicts no default, the probabilities of default and no default are 0.016 and 0.984, respectively.

POINTS: 1 DIFFICULTY: Challenging | Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 09-2 TOPICS: 9.5 Multistage Decision Problems - Bayes' Rule: Probability Approach OTHER: BUSPROG - Analytic |DISC - Decision Making DATE CREATED: 5/17/2017 3:50 PM DATE MODIFIED: 10/21/2017 9:37 PM

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Chapter 10 - Introduction to Simulation Modeling 1. The primary difference between simulation models and other types of spreadsheet models is that simulation models contain ____: a. deterministic inputs b. random numbers c. output cells d. constraints ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.1 Introduction OTHER: BUSPROG - Communication |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 2. Which of the following is not one of the important distinctions of probability distributions? a. Discrete versus continuous b. Symmetric versus skewed c. Bounded versus unbounded d. Positive versus negative ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Types of Probability Distributions OTHER: BUSPROG - Communication |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 3. Discrete distributions are sometimes used in place of continuous distributions: a. because they are more accurate b. because they are simpler c. when we don't know the mean and variance of the distribution d. when we need to generate a histogram ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Types of Probability Distributions OTHER: BUSPROG - Communication |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling DATE MODIFIED: 10/21/2017 9:43 PM 4. The RAND() function in excel models which of the following probability distributions? a. Normal distribution with mean 0 and standard deviation 1 b. Uniform distribution with lower limit 0 and upper limit 1 c. Normal distribution with mean -1 and standard deviation 1 d. Uniform distribution with lower limit -1 and upper limit 1 ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Common Probability Distributions OTHER: BUSPROG - Communication |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 5. If x is a random number between 0 and 1, then we can use x to simulate a variable that is uniformly distributed between 100 and 200 using the formula: a. 100 + x b. 200 − x c. 100 + 100x d. 200x ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Common Probability Distributions OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 6. A distribution for modeling the time it takes to serve a customer at a bank is probably: a. symmetric b. left skewed c. right skewed d. uniform ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Types of Probability Distributions Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 7. Which of the following statements is true regarding the Normal distribution? a. It is always the appropriate distribution in simulation modeling b. It does not permit negative values c. There is a 95% chance that values will be within ± 2 standard deviations of the mean d. All of these options ANSWER: c POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Using @RISK to Explore Probability Distributions OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 8. Which of the following statements is true regarding the Triangular distribution? a. It is a discrete distribution with a minimum, maximum and most likely value b. It is more flexible and intuitive than the normal distribution c. It is a symmetric distribution d. All of these options ANSWER: b POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Using @RISK to Explore Probability Distributions OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 9. When n is reasonably large and p isn't too close to 0 or 1, the binomial distribution can be well approximated by which of the following distributions? a. Uniform distribution b. Normal distribution c. Triangular distribution d. None of these options ANSWER: b POINTS: 1 Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling DIFFICULTY: QUESTION TYPE: HAS VARIABLES: TOPICS:

Challenging |Bloom's Comprehension Multiple Choice False 10.2 Probability Distributions for Input Variables - Using @RISK to Explore Probability Distributions OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 10. If a model contains uncertain outputs, it can be very misleading to build a deterministic model by using the means of the inputs to predict an output. This is called the: a. Law of Large Numbers. b. Flaw of Averages c. Law of Inevitable Disappointment d. Central Limit Theorem ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 10.3 Simulation and the Flaw of Averages OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 11. 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 ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.1 Introduction OTHER: BUSPROG - Communication |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 12. 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 ANSWER: True POINTS: 1 Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Common Probability Distributions OTHER: BUSPROG - Communication |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 13. The three parameters required to specify a triangular distribution are the minimum, mean and maximum. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.2 Probability Distributions for Input Variables - Using @RISK to Explore Probability Distributions OTHER: BUSPROG - Communication |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 14. 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 ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.4 Simulation with Built-in Excel Tools - Notes about Confidence Intervals OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 15. RISKSIMTABLE is an @RISK function for running several simulations simultaneously, one for each setting of an input or decision variable. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling HAS VARIABLES: False TOPICS: 10.5 Introduction to @RISK OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 16. 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 ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.5 Introduction to @RISK - Using Risksimtable OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 17. It is usually fairly straightforward to predict the shape of the output distribution from the shape(s) of the input distribution(s). a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.6 The Effects of the Input Distribution on Results OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 18. 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 ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.6 The Effects of the Input Distribution on Results - Effect of Correlated Input Variables Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 19. A correlation matrix must always be symmetric, so that the correlations above the diagonal are a mirror image of those below it. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.6 The Effects of the Input Distribution on Results - Effect of Correlated Input Variables OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 20. 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 ANSWER: False POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 10.6 The Effects of the Input Distribution on Results - Effect of Correlated Input Variables OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM Exhibit 10-1 A company is in the planning phase of constructing a new production facility. It wants to build a simulation model for the economics of the facility, and one key uncertain input is the construction cost. For each of the scenarios in the questions below, choose an "appropriate" distribution, together with its parameters, and explain your choice.

21. Refer to Exhibit 10-1. Company management currently has no idea what the distribution of the construction cost is.

All they can state is that "we think it will be somewhere between $5,000,000 and $8,000,000."

ANSWER: The "no idea" suggests the uniform distribution, with a lower bound of $5M and an upper bound of $8M. POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling PREFACE NAME: Exhibit 10-1 TOPICS: 10.2 Probability Distributions for Input Variables - Common Probability Distributions OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 22. Refer to Exhibit 10-1. A little later on, management still believes the upper and lower bounds for the costs are $5M and $8M, but now they can also state that "we believe the most likely value is about $6.5M." ANSWER: This suggests a triangular distribution, with a min of $5M, most likely value of $6.5M, and max of $8M. POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 10-1 TOPICS: 10.2 Probability Distributions for Input Variables - Common Probability Distributions OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 23. Refer to Exhibit 10-1. Management believes the facility construction time will be somewhere from 5 to 9 months.

They believe the probabilities of the extremes (5 and 9 months) are both 10%, and the probabilities will vary linearly from those endpoints to a most likely value at 7 months.

ANSWER: This is a general discrete distribution. We just have to choose the probabilities of the values 5 to 9 so that they increase and then decrease linearly, and add up to 1: P(5)=0.1, P(6)=0.225, P(7)=0.35, P(8)=0.225, P(9)=0.1.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 10-1 TOPICS: 10.2 Probability Distributions for Input Variables - Common Probability Distributions OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 24. Refer to Exhibit 10-1. Engineering also believes the construction time will be from 5 to 9 months. However, they believe that 7 months is twice as likely as either 6 months or 8 months and that either of these latter possibilities is three times as likely as either 5 months or 9 months.

ANSWER: This is another general discrete distribution, where we have to choose the probabilities so that they have the specified ratios, and add up to 1: P(5)=0.071, P(6)=0.214, P(7)=0.429, P(8)=0.214, P(9)=0.071.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling PREFACE NAME: Exhibit 10-1 TOPICS: 10.2 Probability Distributions for Input Variables - Common Probability Distributions OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 25. If you add n lognormally distributed random numbers, the mean of the distribution for the sum is the sum of the individual means, and the variance of the distribution of the sum is the individual variances. This result is difficult to prove mathematically, but it is easy to demonstrate with simulation. To do so, run a simulation where you add three lognormally distributed random numbers, with means of 300, 700 and 100, and standard deviations of 20, 50, and 30, respectively. Your single output variable should be the sum of these three numbers. Verify with @RISK that the distribution of this output has a mean of 1,000 and standard deviation .

ANSWER: The output distribution from @RISK yields just about what is expected. This is based on 10,000 iterations.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE Subjective Short Answer : HAS VARIABLES: False TOPICS: 10.6 The Effects of the Input Distribution on Results OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIE 10/21/2017 9:43 PM D: Exhibit 10-2 A large apparel company wants to determine the profitability of one of its most popular products, a particular type of Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling jacket. Demand is uncertain, due to economic conditions, competition, weather and other factors, and the following probability distributions have been estimated for each of the company's three regions: Estimate of Sales in Region 1 Units 9,000 10,000 11,000 12,000 13,000 14,000

Probability 0.05 0.10 0.15 0.35 0.25 0.10

Estimate of Sales in Region 2 Smallest Value: Most Likely Value: Largest Value:

5000 units 7000 units 12000 units

Estimate of Sales in Region 3 Minimum Value: Maximum Value:

6000 units 9000 units

26. 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?

ANSWER:

The above output histogram shows mean expected sales is approximately 27,405 units.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 10-2 TOPICS: 10.6 The Effects of the Input Distribution on Results Copyright Cengage Learning. Powered by Cognero.

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Chapter 10 - Introduction to Simulation Modeling OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 27. 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?

ANSWER: Although the input distributions are different, the combination of the three looks symmetric and fairly normal. The standard deviation is about 2,100 units, and the 5th and 95th percentiles are about 24,000 units and 31,000 units, respectively.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 10-2 TOPICS: 10.6 The Effects of the Input Distribution on Results OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 28. 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)?

ANSWER: Extending the total units sold by the unit price (and making that quantity a simulation output) yields the following output graph. The mean revenue is ˜$1.8M.

POINTS: DIFFICULTY:

1 Moderate |Bloom's Application

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Chapter 10 - Introduction to Simulation Modeling QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 10-2 TOPICS: 10.5 Introduction to @RISK - @RISK Models with Several Random Input Variables OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 29. Refer to Exhibit 10-2. Finally, suppose the apparel company receives an uncertain fraction of the total retail revenue from its retailers, modeled as a Triangular(0.70,0.75,0.80) distribution, and then must subtract production and operations costs, which are modeled as a Lognormal distribution with mean of $1,000,000 and standard deviation of $300,000. In that case, what is the expected net profit from the jacket line?

ANSWER: Applying the fractional multiplier and subtracting the costs from the revenues (and making that quantity a simulation output) yields the following output graph. The mean net profit is just under $370,000.

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 10-2 TOPICS: 10.5 Introduction to @RISK - @RISK Models with Several Random Input Variables OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM 30. 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?

ANSWER: From the histogram, there is approximately a 38% chance of exceeding $0.5M profit.

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Chapter 10 - Introduction to Simulation Modeling

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 10-2 TOPICS: 10.5 Introduction to @RISK - @RISK Models with Several Random Input Variables OTHER: BUSPROG - Analytic |DISC - Intro Simulation DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:43 PM

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Chapter 11 - Simulation Models 1. Which of the following is typically not an application of simulation models? a. Operations models b. Financial models c. Marketing models d. All of the above are applications of simulation models ANSWER: d POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.1 Introduction OTHER: BUSPROG - Communication |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 2. Which of the following is the most likely characteristic of a distribution that is to be used to develop a simulation model for estimating the time until failure of a product in a simulation model? a. Unbounded b. Right skewed c. Normal d. Uniform ANSWER: b POINTS: 1 DIFFICULTY: Moderate | Bloom'sComprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.2 Operations Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 3. Which of the following functions is not an @RISK statistical function? a. RISKMIN b. RISKMAX c. RISKPERCENTILE d. RISKSIMTABLE ANSWER: d POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.2 Operations Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 11 - Simulation Models DATE MODIFIED: 10/21/2017 9:50 PM 4. 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 ANSWER: d POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.2 Operations Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 5. Value at risk (VAR) is an indicator of: a. how much to bid for a project b. the expected amount of loss for a project c. what is nearly the worst possible outcome for a project d. the required amount of investment required for a project ANSWER: c POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 6. 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 ANSWER: POINTS: DIFFICULTY: QUESTION TYPE: HAS VARIABLES:

a 1 Easy | Bloom'sComprehension Multiple Choice False

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Chapter 11 - Simulation Models TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 7. Suppose we compare the difference between the NPV of a financial model in which the means are entered for all input random variables and the NPV of a financial model in which the most likely values are entered for all input random variables. If we see a large difference between the NPV's, this illustrates: a. the value at risk (VAR) b. the effect of randomness c. the flaw of averages d. the bias of the analyst ANSWER: c POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 8. 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 ANSWER: c POINTS: 1 DIFFICULTY: Easy | Bloom'sApplication QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 9. A key input variable in many marketing models of customer loyalty is the: a. Mean profit per customer b. Number of customers c. Churn rate d. Time horizon ANSWER: c POINTS: 1 Copyright Cengage Learning. Powered by Cognero.

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Chapter 11 - Simulation Models DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.4 Marketing Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 10. The main issue in marketing and sales models is: a. the amount invested in marketing b. the timing of marketing c. the profit from sales d. the timing of sales ANSWER: d POINTS: 1 DIFFICULTY: Moderate | Bloom'sComprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 11.4 Marketing Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 11. In bidding models, the simulation output variable is the number of competitors who will bid. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.2 Operations Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 12. In warranty cost models, the key input random variable is product lifetime. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: True / False HAS VARIABLES: False Copyright Cengage Learning. Powered by Cognero.

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Chapter 11 - Simulation Models TOPICS: 11.2 Operations Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 13. A common distribution for modeling product lifetimes is the normal distribution a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.2 Operations Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 14. The RISKSIMTABLE function is used to summarize the results of a single simulation of product lifetime. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.2 Operations Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 15. RISKTARGET is a function that allows us to determine the cumulative probability of a particular value in an output distribution, such as the probability of meeting a due date in manufacturing. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy | Bloom'sComprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.2 Operations Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 11 - Simulation Models 16. 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 ANSWER: False POINTS: 1 DIFFICULTY: Moderate | Bloom'sApplication QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 17. A tornado chart lets us see which random input has the most effect on a specified output in a financial model. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy | Bloom'sApplication QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 18. A marketing simulation model can be used to determine the expected profit under uncertain customer loyalty, but an optimization model must be used to determine the optimal amount to spend on increasing customer loyalty. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate | Bloom'sApplication QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.4 Marketing Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 19. In marketing and sales models, the primary issue is the uncertain amount of sales that can be obtained, given an assumed timing. a. True Copyright Cengage Learning. Powered by Cognero.

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Chapter 11 - Simulation Models b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate | Bloom'sApplication QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.4 Marketing Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 20. A @RISK output range allows us to obtain a summary chart that shows the entire simulated range at once. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy | Bloom'sApplication QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 11.4 Marketing Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM Exhibit 11-1 A company is considering investing $1.2M in a facility to manufacture a new product. The product will have a five year life, after which the facility will be shut down. A pro forma cash flow sheet for this project, with forecasted production levels, unit prices, and production costs, is shown below:

21. [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?

ANSWER: Including the required investment of $1.2 million, the resulting NPV is $281,500.

POINTS: 1 DIFFICULTY: Easy | Bloom'sApplication QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-1 TOPICS: 11.3 Financial Models Copyright Cengage Learning. Powered by Cognero.

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Chapter 11 - Simulation Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 22. [Part 2] Refer to Exhibit 11-1. Suppose that the forecasted price levels shown in the pro forma cash flow sheet are not deterministic, but rather are expected to fluctuate due to market forces. The prices are expected to be normally distributed in each year, with the following means and standard deviations:

Using the appropriate @RISK functions in the pro forma, what is the expected NPV? Would you recommend investing in this project? Explain.

ANSWER: The mean NPV will still be approximately $282,000. Since the NPV is positive, the project looks like a good investment; however, we should also look at the risk involved.

POINTS: 1 DIFFICULTY: Moderate | Bloom'sApplication QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-1 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 23. [Part 3] Refer to Exhibit 11-1. What is the standard deviation of the NPV? What does it indicate?

ANSWER: The standard deviation of the NPV is approximately $707,000. It indicates a fairly wide range of dispersion of outcomes in this case, which means the project is fairly risky.

POINTS: 1 DIFFICULTY: Easy | Bloom'sApplication QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-1 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 24. [Part 4] Refer to Exhibit 11-1. What does the distribution of the project NPV look like?

ANSWER: The distribution is nearly symmetric, with a large range, including many negative values.

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Chapter 11 - Simulation Models

POINTS: 1 DIFFICULTY: Easy | Bloom'sApplication QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-1 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 25. [Part 5] Refer to Exhibit 11-1. What are the chances the firm could lose money on this project, given the price uncertainty?

ANSWER: The output graph below indicates about a 34% chance of a NPV below zero.

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Chapter 11 - Simulation Models

POINTS: 1 DIFFICULTY: Easy | Bloom'sApplication QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-1 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 26. [Part 6] Refer to Exhibit 11-1. Given your answers to Parts 1 through 5, would you invest in this project?

ANSWER: Although this project has a positive NPV, there is also substantial risk involved. A firm with a relatively low tolerance for risk may indeed decide not to pursue this project.

POINTS: 1 DIFFICULTY: Easy | Bloom'sApplication QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-1 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM Exhibit 11-2 Suppose we want to choose capacity for a plant that will produce a new drug. In particular, we want to choose the capacity that maximizes discounted expected profit over the next 10 years. Assume all cash flows occur at the end of the year. We have the following information: Copyright Cengage Learning. Powered by Cognero.

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Chapter 11 - Simulation Models ∙ ∙ ∙ ∙ ∙ ∙

Demand for the drug is expected to be normally distributed ˜ Normal (50,000, 12,000).

Demand each year is an independent event.

A unit of capacity costs $16 to build in year 1.

The number of units produced will equal the demand, up to capacity limits.

The revenue per unit is $3.70 and the cost per unit is $0.20 (variable cost).

The maintenance cost per unit of capacity is $0.40 (fixed cost).

The discount rate is 10%.

27. [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?

ANSWER: The output below shows an expected NPV of $49,474.

POINTS: 1 DIFFICULTY: Moderate | Bloom'sApplication QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-2 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 28. [Part 2] Refer to Exhibit 11-2. Use a RISKSIMTABLE to with the following values for capacity: 20,000, 25,000, 30,000, 35,000, 40,000. Which of these capacities produces the largest expected NPV?

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Chapter 11 - Simulation Models ANSWER:

Simulation 4 (capacity = 35,000 units) yields the largest mean NPV of $93,653.

POINTS: 1 DIFFICULTY: Moderate | Bloom'sApplication QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-2 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 29. [Part 3] Refer to Exhibit 11-2. Briefly explain why designing the plant for the expected capacity is clearly not the optimal solution.

ANSWER: We can see from the plot in the answer to Part 1 that the NPV distribution is skewed to the left (i.e., includes some very negative outcomes). The cost of over-designing the plant outweighs the opportunity cost of lost sales if the plant is designed too small to meet demand.

POINTS: 1 DIFFICULTY: Moderate | Bloom'sAnalysis Copyright Cengage Learning. Powered by Cognero.

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Chapter 11 - Simulation Models QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-2 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM 30. [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.

ANSWER: Yes. Both simulations 4 and 5 (Q=35,000 units and Q=40,000 units) have a minimum that is negative, so there is at least some chance of getting a negative number with these alternatives (although the smallest percentile, 5th percentile, was still positive in both cases).

POINTS: 1 DIFFICULTY: Easy | Bloom'sAnalysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 11-2 TOPICS: 11.3 Financial Models OTHER: BUSPROG - Analytic |DISC - Simulation Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:50 PM

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Chapter 12 - Queueing Models 1. 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 ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.2 Elements of Queueing Models OTHER: BUSPROG - Communication |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 2. When a customer already in line in a queuing system becomes impatient and leaves the system before starting service, this is called: a. balking b. limited waiting c. quitting d. reneging ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.2 Elements of Queueing Models - Characteristics of Arrivals OTHER: BUSPROG - Communication |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 3. 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 ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.2 Elements of Queueing Models - Service Discipline OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 12 - Queueing Models DATE MODIFIED: 10/21/2017 9:56 PM 4. A queuing system where customers join a single line and then are served by the first available server are said to be: a. in parallel b. in series c. random d. networked ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.2 Elements of Queueing Models - Service Characteristics OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 5. A requirement for steady state analysis of a queuing system is that: a. the initial conditions are still in effect b. the waiting time must be exponentially distributed c. the analysis period is at least two hours d. the service rate must be constant ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.2 Elements of Queueing Models - Service Characteristics OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 6. The exponential distribution is: a. flat b. bell-shaped c. heavily right-skewed d. heavily left-skewed ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.3 The Exponential Distribution OTHER: BUSPROG - Analytic |Queueing Copyright Cengage Learning. Powered by Cognero.

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Chapter 12 - Queueing Models DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 7. The parameter λ in an exponential distribution can be interpreted as a: a. time b. rate c. mean d. standard deviation ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.3 The Exponential Distribution OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 8. 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 ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.4 Important Queueing Relationships OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 9. 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 ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.5 Analytic Steady-State Queueing Models Copyright Cengage Learning. Powered by Cognero.

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Chapter 12 - Queueing Models OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 10. As the traffic intensity approaches 1: a. there is no waiting b. waiting lines stabilize c. waiting lines grow extremely rapidly d. at least one server will be idle ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 12.5 Analytic Steady-State Queueing Models OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 11. The two basic modeling approaches for queuing systems are optimization and simulation. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.1 Introduction OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 12. Almost all queuing systems are alike in that customers enter a system, possibly wait in one or more queues, get served, and then depart. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.2 Elements of Queueing Models OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 12 - Queueing Models DATE MODIFIED: 10/21/2017 9:56 PM 13. The decision to balk at entering a queuing system can be made by the customer or the system. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.2 Elements of Queueing Models - Characteristics of Arrivals OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 14. The mean and standard deviation of an exponential distribution are both equal to the parameter λ. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.3 The Exponential Distribution OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 15. In a process where interarrival times are exponentially distributed, the time since the last arrival is irrelevant. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.3 The Exponential Distribution - The Memoryless Property OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 16. Exponentially distributed service times are often more realistic than exponentially distributed interarrival times. a. True b. False Copyright Cengage Learning. Powered by Cognero.

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Chapter 12 - Queueing Models ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.3 The Exponential Distribution OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 17.

The server utilization U in an M/M/s system is always the same as the traffic intensity. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.5 Analytic Steady-State Queueing Models - The Basic Multiple Server Model OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 18. In queuing systems with a finite number of customers allowed, there is no need to require that the traffic intensity be less than 1 to ensure stability. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.5 Analytic Steady-State Queueing Models - Other Exponential Models OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 19. In an Erlang loss model, customers who arrive when all servers are busy are lost to the system. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension Copyright Cengage Learning. Powered by Cognero.

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Chapter 12 - Queueing Models QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.5 Analytic Steady-State Queueing Models - Erlang Loss Model OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 20. Congestion in a queuing system will be unaffected by changes in the variability of the interarrival time and service time distributions, as long as the distributions retain the same means. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 12.6 Queueing Simulation Models - Fundamental Insight OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM Exhibit 12-1 A grocery store manager would like to use an analytical queueing model to study the lines of customers that form in front of the checkout stations in the store. During a period of time when business is steady, several store employees have gathered data on customer interarrival times, which are shown below.

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Chapter 12 - Queueing Models

21. [Part 1] Refer to Exhibit 12-1. Is it reasonable to assume exponentially distributed interarrival times for the grocery store customers? If so, what is λ?

ANSWER: The histogram of the data (shown below) appears to be consistent with the exponential density. The mean of the data is ˜5, so the parameter λ = 0.2.

POINTS:

1

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Chapter 12 - Queueing Models DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 12-1 TOPICS: 12.3 The Exponential Distribution OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 22. [Part 2] Refer to Exhibit 12-1. Assuming an exponential distribution with the parameter λ you obtained in Part 1, what is the probability that a customer interarrival time will be less than 2 minutes?

ANSWER: =EXPON.DIST(2,0.2,true) = 0.33

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 12-1 TOPICS: 12.3 The Exponential Distribution OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 23. [Part 3] Refer to Exhibit 12-1. Again assuming an exponential distribution with the parameter λ 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?

ANSWER: =EXPON.DIST(5,0.2,TRUE)-EXPON.DIST(2,0.2,TRUE) = 0.632 − 0.330 = 0.302

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Chapter 12 - Queueing Models

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 12-1 TOPICS: 12.3 The Exponential Distribution OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM Exhibit 12-2 An oil-change facility serves customers that enter at a rate of 8 per hour. There are five servers available to perform oil changes for entering customers. Customers wait in a single line and enter the facility, in first-come-first-serve fashion, to the first of the five servers who is available. Each server can change the oil of one customer's car every 30 minutes on average.

24. Refer to Exhibit 12-2. How many of the servers are busy on average?

ANSWER: Ls = λ * Ws = 8 * 0.5 = 4 customers, so 4 servers would be busy serving them.

POINTS: DIFFICULTY: QUESTION TYPE: HAS VARIABLES: PREFACE NAME: TOPICS: OTHER: DATE CREATED:

1 Easy |Bloom's Application Subjective Short Answer False Exhibit 12-2 12.4 Important Queueing Relationships BUSPROG - Analytic |Queueing 5/17/2017 3:51 PM

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Chapter 12 - Queueing Models DATE MODIFIED: 10/21/2017 9:56 PM 25. Refer to Exhibit 12-2. What is the server utilization?

ANSWER: U = Ls / s = 4 / 5 = 0.8.

POINTS: 1 DIFFICULTY: Easy |Bloom's Application QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 12-2 TOPICS: 12.4 Important Queueing Relationships OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM Exhibit 12-3 A Credit Union has a small branch in which a single customer service representative serves the needs of customers who arrive at an average rate of 24 per hour. The service representative can typically handle 30 customers per hour. Based on an analysis of historical data, it is reasonable to assume that customer interarrival times and service times are exponentially distributed. Assume that all arriving customers enter the branch, regardless of the number already waiting in line.

26. Refer to Exhibit 12-3. What is the average length of the waiting line?

ANSWER: ρ = λ / μ = 24 / 30 = 0.8 L = ρ / (1− ρ) = 0.8/(1 − 0.8) = 4 customers W = L / λ = 4 / 24 = 0.167 hours WQ = W −1/ μ = 0.167 − (1 / 30) = 0.133 hours LQ = λ * WQ = 24 * 0.133 = 3.2 customers POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 12-3 TOPICS: 12.5 Analytic Steady State Queueing Models - The Basic Single Server Model OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 27. Refer to Exhibit 12-3. What is the average length of time (in hours) spent waiting in line?

ANSWER: WQ = WS − 1/ μ = 0.167 − (1 / 30) = 0.133 hours POINTS: DIFFICULTY: QUESTION TYPE: HAS VARIABLES: PREFACE NAME: TOPICS:

1 Easy |Bloom's Analysis Subjective Short Answer False Exhibit 12-3 12.5 Analytic Steady State Queueing Models - The Basic Single Server Model

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Chapter 12 - Queueing Models OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 28. Refer to Exhibit 12-3. What percentage of all customers have to spend at least some small amount of time waiting in line?

ANSWER: % waiting in queue = 1 − ρ = 20% → % spending some time in queue = 1 − 20% = 80% POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 12-3 TOPICS: 12.5 Analytic Steady State Queueing Models - The Basic Single Server Model OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM Exhibit 12-4 Consider a fast-food restaurant where customers arrive at a Poisson rate of 100 per hour. Four equally capable servers work at the restaurant during a typical hour of operation. Each employee takes, on average, 2 minutes to serve a customer, and service times are exponentially distributed. Customers who arrive and find all 4 servers busy join a single queue and are then served in first-come-first-served fashion.

29. 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 ANSWER: The expected number of busy servers = expected number in system − expected number in queue = 4.029 − 0.696 = 3.333. The expected fraction of time each server is busy is then 3.333/4 servers = 0.833 POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 12-4 TOPICS: 12.5 Analytic Steady State Queueing Models - The Basic Multiple Server Model OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM 30. Refer to Exhibit 12-4. What percentage of customers do not wait in the queue?

ANSWER: The expected % of customers that do not wait = 34.2 % POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 12-4 Copyright Cengage Learning. Powered by Cognero.

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Chapter 12 - Queueing Models TOPICS: 12.5 Analytic Steady State Queueing Models - The Basic Multiple Server Model OTHER: BUSPROG - Analytic |Queueing DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 9:56 PM

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Chapter 13 - Regression and Forecasting Models 1. Forecasting models can be divided into three groups. They are: a. time series, optimization, and simulation methods b. judgmental, regression, and extrapolation methods c. judgmental, random, and linear methods d. linear, non-linear, and extrapolation methods ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.1 Introduction OTHER: BUSPROG - Communication |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 2. In regression analysis, the variable we are trying to explain or predict is called the a. independent variable b. dependent variable c. regression variable d. statistical variable ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.2 Overview of Regression Models OTHER: BUSPROG - Communication |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 3. In multiple regression, the regression coefficients reflect the expected change in: a. Y when the associated X value increases by one unit, holding the other variables constant b. X when the associated Y value increases by one unit, holding the other variables constant c. Y when the associated X value decreases by one unit, holding the other variables constant d. X when the associated Y value decreases by one unit, holding the other variables constant ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Evaluation QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.4 Multiple Regression Models OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models 4. The biggest challenge of regression is: a. differentiating the independent variable(s) from the dependent variable(s) b. determining which independent variable(s) to include c. collecting accurate data d. properly coding the variables ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Evaluation QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.4 Multiple Regression Models OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 5. The adjusted R2 adjusts R2 for: a. non-linearity b. outliers c. low correlation d. the number of explanatory variables in a multiple regression model ANSWER: d POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.4 Multiple Regression Models - Solution OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 6. A "fan" shape in a scatterplot indicates: a. nonconstant error variance b. a nonlinear relationship c. the absence of outliers d. sampling error ANSWER: a POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.4 Multiple Regression Models - A Caution about Regression Assumptions OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models DATE MODIFIED: 10/21/2017 10:04 PM 7. The term autocorrelation refers to: a. the analyzed data refers to itself b. the sample is related too closely to the population c. the data are in a loop (values repeat themselves) d. time series variables are usually related to their own past values ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.4 Multiple Regression Models - A Caution about Regression Assumptions OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 8. 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) ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.5 Overview of Time Series Models - Measures of Forecast Error OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 9. When using the moving average method, you must select ____ which represent(s) the number of terms in the moving average. a. a smoothing constant b. the explanatory variables c. an alpha value d. a span ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.6 Moving Average Models Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 10. A model that uses temperature, season of the year (fall, winter, spring, summer), and whether or not it is a weekend, to predict the # of customers for the day would include how many independent variables? a. 3 b. 5 c. 6 d. 7 ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 13.7 Exponential Smoothing Models - Winter's Method for Seasonality OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 11. The residual is defined as the difference between the actual and predicted, or fitted values of the response variable. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.2 Overview of Regression Models - The Least Squares Line OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 12. The least squares line is the line that minimizes the sum of the residuals. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.2 Overview of Regression Models - The Least Squares Line OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models DATE MODIFIED: 10/21/2017 10:04 PM 13. A useful graph in almost any regression analysis is a scatterplot of residuals (on the vertical axis) versus fitted values (on the horizontal axis), where a "good" fit not only has small residuals, but it has residuals scattered randomly around zero with no apparent pattern. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.3 Simple Regression Models - Discussion of the Results OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 14. In reference to the equation , the value 0.10 is the expected change in Y per unit change in X. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Evaluation QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.3 Simple Regression Models OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 15. 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 ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.2 Overview of Regression Models - Measures of Goodness of Fit OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models 16. The percentage of variation explained R2 is the square of the correlation between the observed Y values and the fitted Y values. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.4 Multiple Regression Models - Discussion of the Results OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 17. The adjusted R2 is used primarily to monitor whether extra explanatory variables really belong in a multiple regression model. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.4 Multiple Regression Models - Discussion of the Results OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 18. A time series can consist of four different components: trend, seasonal, cyclical, and random (or noise). a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.5 Overview of Time Series Models OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 19. The smoothing constant used in simple exponential smoothing is analogous to the span in moving averages. a. True b. False Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.7 Exponential Smoothing Models - Simple Exponential Smoothing OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 20. Winter's method is an exponential smoothing method, which is appropriate for a series with trend but no seasonality. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 13.7 Exponential Smoothing Models - Winter's Method for Seasonality OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM Exhibit 13-1 An express delivery service company recently conducted a study to investigate the relationship between the cost of shipping a package (Y), the package weight in pounds (X1), and the distance shipped in miles (X2). Twenty packages were randomly selected from among the large number received for shipment, and a detailed analysis of the shipping cost was conducted for each package. The sample information is shown in the table below:

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Chapter 13 - Regression and Forecasting Models

21. 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 R2.

ANSWER:

As the package weight increases by one pound, the cost of shipping the package increases by $1.49 on average. This simple linear regression model explains 59.85% of the total variation in the cost of shipment.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-1 TOPICS: 13.3 Simple Regression Models - Discussion of the Results OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models 22. Refer to Exhibit 13-1. Add the second explanatory variable (distance shipped) to the regression model. Estimate and interpret the slopes of this expanded model.

ANSWER:

Now, holding all else constant, the cost of shipping a package rises by approximately $1.29 when the package weight increases by one pound. Furthermore, holding all else constant, the cost of shipping a package rises by approximately $0.04 when the distance shipped increases by one mile.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-1 TOPICS: 13.4 Multiple Regression Models - Discussion of the Results OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 23. Refer to Exhibit 13-1. How does the R2 value for this multiple regression model compare to that of the simple regression model estimated above? Interpret the adjusted R2 values for the two models.

ANSWER: Both the R2 and adjusted R2 values have increased considerably with the addition of the second explanatory variable; the multiple regression model fits the given data better than did the simple linear model. The R2 and adjusted R2 values are quite similar for the multiple regression model.

Therefore, both explanatory variables are adding to the explanation of the variation in the cost of shipment.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-1 TOPICS: 13.4 Multiple Regression Models - Discussion of the Results OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM Exhibit 13-2 Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models The station manager of a local television station is interested in predicting the amount of television (in hours) that people will watch in the viewing area. The explanatory variables are: X1 age (in years), X2 education (highest level obtained, in years) and X3 family size (number of family members in household). The multiple regression output is shown below: Summary measures Multiple R 0.8440 R-Square 0.7123 Adj R-Square 0.6644 StErr of 0.5598 Estimate ANOVA Table Source df Explained 3 Unexplained 18

SS 13.9682 5.6413

MS 4.6561 0.3134

F 14.8564

p-value 0.0000

Regression coefficients Constant Age Education Family Size

Coefficient 1.683 −0.0498 0.2135 0.0405

Std Err 1.1696 0.0199 0.0503 0.0784

t-value 1.4389 −2.5018 4.2426 0.5168

p-value 0.1674 0.0222 0.0005 0.6116

24. Refer to Exhibit 13-2. Use the information above to estimate the linear regression model.

ANSWER: POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-2 TOPICS: 13.4 Multiple Regression Models - Discussion of the Results OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 25. Refer to Exhibit 13-2. Interpret each of the estimated regression coefficients of the regression model above.

ANSWER: This model shows that the number of hours people spend watching television decreases by 0.0498 hours on average with every additional year in age (while holding education level and family size constant); increases by 0.2135 hours on average with a person's education level increasing by one year (while holding age and family size constant), and increases by 0.0405 hours on average as the family size increases by one person (while holding age and education level constant).

POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-2 TOPICS: 13.4 Multiple Regression Models - Discussion of the Results Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 26. Refer to Exhibit 13-2. Identify and interpret the percentage of variation explained (R2) for the model.

ANSWER: The percentage of variation explained R2 = 0.7123; this represents 71.23% of the variation in the hours spent watching television can be explained by this regression equation.

POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-2 TOPICS: 13.4 Multiple Regression Models - Discussion of the Results OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM Exhibit 13-3 The quarterly numbers of applications for home mortgage loans at a branch office of a large bank are recorded in the table below.

Quarter-Year Applications 1-13 96 2-13 114 3-13 112 4-13 81 1-14 97 2-14 103 3-14 120 4-14 99 1-15 105 2-15 110 3-15 117 4-15 96 1-16 74 2-16 94 3-16 100 4-16 96 1-17 95 2-17 122 3-17 113 4-17 100 1-18 102 2-18 96 Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models 3-18 4-18

116 98

27. 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? ANSWER: There is no apparent trend or seasonality, so a simple smoothing model (moving average or simple exponential smoothing) is a reasonable choice. It appears the data are random, so it may be difficult to find a model that fits well.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-3 TOPICS: 13.5 Overview of Time Series Models OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 28. 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 13 - Regression and Forecasting Models ANSWER:

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-3 TOPICS: 13.6 Moving Average Models OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:04 PM 29. Refer to Exhibit 13-3. Use simple exponential smoothing to forecast these data, requesting 4 quarters of future forecasts. Use the default smoothing constant of 0.10. Is this better than the moving average model?

ANSWER: The MAPE has increased from 9.24% to 9.5%, so this model fits the data worse than the moving average model.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-3 TOPICS: 13.7 Exponential Smoothing Models - Simple Exponential Smoothing OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:52 PM Copyright Cengage Learning. Powered by Cognero.

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Chapter 13 - Regression and Forecasting Models DATE MODIFIED: 10/21/2017 10:04 PM

30. 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?

ANSWER: It doesn't seem to matter much whether we use a smoothing constant of 0.10 or the optimal smoothing constant (which turns out to be 0.079). Neither model fits the data very well, and the MAPE is still higher than the MAPE for the moving average model.

POINTS: 1 DIFFICULTY: Easy |Bloom's Analysis QUESTION TYPE: Subjective Short Answer HAS VARIABLES: False PREFACE NAME: Exhibit 13-3 TOPICS: 13.7 Exponential Smoothing Models - Simple Exponential Smoothing OTHER: BUSPROG - Analytic |DISC - Regression and Forecasting DATE CREATED: 5/17/2017 3:52 PM DATE MODIFIED:10/21/2017 10:04 PM

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Chapter 14 - Data Mining True / False 1. Today's organizations rely on their quantitative experts, who have access to large amounts of data, to make sense of it in a timely manner. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.1 Introduction OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 6:47 PM DATE MODIFIED: 10/21/2017 10:11 PM 2. If the probability of a restaurant being successful is 10% then the odds of it failing are 10 to 1. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.2 Classification Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 6:53 PM DATE MODIFIED: 10/21/2017 10:15 PM 3. Naive Bayes method assumes probabilistic independence across characteristics which means that the joint probability is the product of the probabilities of the individual characteristics. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.1 Introduction OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 7:15 PM DATE MODIFIED: 10/21/2017 10:11 PM 4. Better classification methods should improve lift, which is the increase in purchases gained through marketing to people with the highest probability of purchasing.

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Chapter 14 - Data Mining a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Logistic Regression OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 7:23 PM DATE MODIFIED: 10/21/2017 10:11 PM 5. When classifying rare events, it is inadvisable to oversample. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Neural Networks OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 7:28 PM DATE MODIFIED: 10/21/2017 10:11 PM 6. The function INDEX(A1:E5,4,3) would return the value in cell C4. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.2 Classification Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 7:34 PM DATE MODIFIED: 10/21/2017 10:11 PM 7. The last step of cluster analysis is to understand the shared characteristics of the observations in each cluster. a. True b. False ANSWER: POINTS:

True 1

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Chapter 14 - Data Mining DIFFICULTY: Moderate |Bloom's Knowledge QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Measures of Classification Accuracy OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 7:42 PM DATE MODIFIED: 10/21/2017 10:11 PM 8. Business analytics, while important, is only a part of the area of data mining. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 7:45 PM DATE MODIFIED: 10/21/2017 10:11 PM 9. In data partitioning, data can be divided into training, testing, and prediction subsets. a. True b. False ANSWER: True POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 7:50 PM DATE MODIFIED: 10/21/2017 10:11 PM 10. The primary advantage of neural networks is that they provide more accurate predictions, especially when the relationships are linear. a. True b. False ANSWER: False POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: True / False HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Logistic Regression Copyright Cengage Learning. Powered by Cognero.

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Chapter 14 - Data Mining OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 7:53 PM DATE MODIFIED: 10/21/2017 10:11 PM Multiple Choice 11. 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.

ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.1 Introduction OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 3:33 PM DATE MODIFIED: 10/21/2017 10:11 PM 12. SQL Server Analysis Services (SSAS) concentrates on which types of data mining? a. classification and clustering b. market basket and forecasting c. clustering and prediction d. forecasting and classification ANSWER: a POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Logistic Regression OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 3:36 PM DATE MODIFIED: 10/21/2017 10:11 PM 13. In the classification method, when data are partitioned into the training and testing subsets: a. the data are divided evenly into the subsets. b. the values of the dependent variable are known for both the training and the testing subsets. c. the records in the subsets are chosen based on similar characteristics. d. all of the above.

ANSWER: b POINTS: 1 DIFFICULTY: Moderate |Bloom's Comprehension Copyright Cengage Learning. Powered by Cognero.

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Chapter 14 - Data Mining QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Naïve Bayes OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 3:38 PM DATE MODIFIED: 10/21/2017 10:11 PM 14. For logistic regression: a. the odds ratio is the independent variable. b. the primary objective is to score each member. c. the cutoff value is set to 0.5. d. the magnitude of the regression coefficients can be compared for relative importance.

ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Knowledge QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Measures of Classification Accuracy OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 3:41 PM DATE MODIFIED: 10/21/2017 10:11 PM 15. Which of the following is false regarding neural networks? a. They attempt to mimic the complex behavior of the human brain. b. They are synonymous with data mining. c. They can be used to predict the value of a numeric dependent variable. d. They do not provide an understanding of the contributions of individual explanatory variables.

ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Classification with Rare Events OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 3:45 PM DATE MODIFIED: 10/21/2017 10:11 PM 16. Which of the following is not a classification method? a. Naive Bayes b. Logistic regression c. ROC curves d. Neural networks ANSWER: c Copyright Cengage Learning. Powered by Cognero.

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Chapter 14 - Data Mining POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 3:51 PM DATE MODIFIED: 10/21/2017 10:11 PM 17. Specificity, a measure of classification accuracy, reflects: (regard class 1 as yes and class 2 as no) a. the portion of observations that are actually in class 1 that are classified as being in class 1. b. the portion of observations that are actually in class 2 that are classified as being in class 2. c. the portion of observations that are actually in class 2 that are classified as being in class 1. d. the portion of observations that are classified as class 1 that are actually in class 1.

ANSWER: b POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 4:03 PM DATE MODIFIED: 10/21/2017 10:11 PM 18. Which of the following is true of clustering methods? a. They are called supervised data mining techniques. b. They require known values of the dependent variable. c. They group observations into clusters based on predefined characteristics. d. They are also known as segmentation methods.

ANSWER: d POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.4 Conclusion OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 4:11 PM DATE MODIFIED: 10/21/2017 10:11 PM 19. 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.

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Chapter 14 - Data Mining d. cannot be directly implemented in Excel.

ANSWER: a POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.2 Classification Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 6:28 PM DATE MODIFIED: 10/21/2017 10:11 PM 20. The logistic function 1/(1+e -x ) a. is concave. b. is convex. c. is S-shaped. d. takes on values between -1 and 1.

ANSWER: c POINTS: 1 DIFFICULTY: Easy |Bloom's Comprehension QUESTION TYPE: Multiple Choice HAS VARIABLES: False TOPICS: 14.2 Classification Methods - Neural Networks OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 6:39 PM DATE MODIFIED: 10/21/2017 10:11 PM Completion

Exhibit 14.1 The age, weight, gender, and the number of children were tracked for 50 people who either have or have not been diagnosed with a certain illness. The data are provided in the table below.

person 1 2 3 4 5 6 7 8 9 10 11

age 67 54 36 29 34 22 72 41 46 41 34

weight 202 190 132 139 143 194 174 140 152 172 190

gender f f f f f m f f m f f

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children 0 0 0 1 1 1 1 4 4 2 5

illness n y n n n y y n n y n Page 7

Chapter 14 - Data Mining

12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

59 46 53 60 29 50 64 52 56 37 46 27 64 55 79 67 72 58 74 43 42 28 60 60 62 57 31 68 26 38 51 62 38 73 48 54 38 54 52

179 123 126 232 236 217 155 217 171 171 168 183 173 200 203 212 224 217 194 177 178 183 177 176 199 177 152 185 134 142 199 133 131 196 120 197 136 183 199

f f f m m m m m m m m m m m m m m m m m m m f m m m f f f f f f f m f f f f f

2 3 3 0 0 0 1 1 4 4 2 2 2 3 1 3 2 2 2 4 1 1 1 5 0 0 3 2 2 2 2 4 4 1 2 1 0 0 0

y n n y y y y y n n n n n n y y y y y n n n y n n n n n n n n n n y n y n y y

21. See Exhibit 14.1 - How well can logistic regression classify the people as having the illness or not?

ANSWER: The logistic regression model correctly classifies the people 94.0% of the time. This is an 86.96% improvement over classifying them all as having the illness.

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Chapter 14 - Data Mining

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Completion HAS VARIABLES: False PREFACE NAME: Exhibit 14.1 TOPICS: 14.2 Classification Methods - Logistic Regression OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/9/2017 10:12 PM DATE MODIFIED: 10/21/2017 10:11 PM 22. See Exhibit 14.1 - What kind of person is more likely to be diagnosed with the illness?

ANSWER: Based on the slopes, older, heavier women with fewer children are more likely to have the illness.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYP Completion E: HAS VARIABLESFalse : PREFACE NAMEExhibit 14.1 : TOPICS: 14.2 Classification Methods - Logistic Regression OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED 10/9/2017 10:27 PM : DATE MODIFIED 10/21/2017 10:11 PM : 23. 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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Chapter 14 - Data Mining ANSWER:

POINTS: 1 DIFFICULTY: Moderate |Bloom's Analysis QUESTION TYP Completion E: HAS VARIABLE False S: PREFACE NAM Exhibit 14.1 E: TOPICS: 14.2 Classification Methods - Logistic Regression OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED10/9/2017 10:31 PM : DATE MODIFIE 10/21/2017 10:11 PM D: 24. 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?

ANSWER: For the training set, 12% of those who have not been diagnosed were incorrectly classified and 26.7% of those who have been diagnosed were incorrectly classified.

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Completion HAS VARIABLES: False PREFACE NAME: Exhibit 14.1 TOPICS: 14.2 Classification Methods - Neural Networks Copyright Cengage Learning. Powered by Cognero.

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Chapter 14 - Data Mining OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/12/2017 3:43 PM DATE MODIFIED: 10/21/2017 10:11 PM

Exhibit 14.2 The age, weight, gender, and the number of children were tracked for 25 people. It is not known if these people have or have not been diagnosed with a certain illness. The data are provided in the table below.

person 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75

age 52 72 33 60 65 71 26 63 23 52 28 59 48 51 71 26 34 56 65 62 49 71 21 51 21

weight 86 145 113 167 134 198 120 165 155 152 183 177 184 201 181 179 115 176 126 181 157 165 138 187 119

gender m f f m f m f m f f m m m m m m f m m f m f f m f

children illness 2 2 2 0 1 2 1 2 1 1 3 1 2 0 2 0 1 1 2 1 1 0 2 0 1

25. See Exhibit 14-2 Using Palisade's NeuralTools and the results from the prior problem, use the prediction data in this table to classify these 25 people as having been diagnosed with an illness or not.

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Chapter 14 - Data Mining ANSWER:

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYP Completion E: HAS VARIABLE False S: PREFACE NAM Exhibit 14.2 E: TOPICS: 14.2 Classification Methods - Neural Networks OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATE 10/12/2017 3:53 PM D: DATE MODIFIE 10/21/2017 10:11 PM D:

Exhibit 14-3 Information for 26 colleges and universities in the state of Indiana is provided in the table below. The following Copyright Cengage Learning. Powered by Cognero.

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Chapter 14 - Data Mining

questions contain a sequence of steps for executing the K-Means Clustering Method.

66% 62% 73% 65% 58% 78% 68% 57% 86% 79% 69%

In State Tuition $ 29,710 $ 9,774 $ 40,175 $ 47,838 $ 45,750 $ 30,920 $ 33,200 $ 36,520 $ 8,916 $ 10,533 $ 7,207

ACT Composit 22 22 27.5 26.5 28 22 25.5 25 19 27 20.5

11453

98%

$ 8,330

21.5

Public

21748

74%

$ 9,334

22.5

Public Public Private Public Private Private Private Private Private Private Public Private Private

6653 5486 2147 30043 2202 2131 3372 2348 4346 8530 7956 3294 843

77% 84% 59% 56% 61% 80% 77% 71% 88% 19% 92% 83% 63%

$ 7,207 $ 7,207 $ 33,000 $ 9,992 $ 47,997 $ 32,885 $ 31,540 $ 35,396 $ 28,390 $ 51,505 $ 7,900 $ 38,760 $ 42,250

20.5 20 22 28 29.5 25.5 23.5 26 23 32.5 22 26 25.5

Name

Type

UG Enrollment Admission rate

Anderson University Ball State University Butler University Depauw University Earlham College Franklin College Goshen College Hanover College Indiana State University Indiana University Indiana University Kokomo Indiana University Purdue University Fort Wayne Indiana University Purdue University Indianapolis Indiana University Southbend Indiana University Southeast Marian University Purdue University Rose Hulman Institute of Technology Taylor University Trine University University of Evansville University of Indianapolis University of Notre Dame University of Southern Indiana Valparaiso University Wabash College

Private Public Private Private Private Private Private Private Public Public Public

1883 17011 4290 2225 1031 1016 800 1090 11202 29184 3977

Public

26. Refer to exhibit 14-3 As a first step in grouping the Indiana colleges and universities into clusters, standardize the numeric measures. (observation minus mean)/standard deviation for each numeric measure ANSWER:

Standardized data UG ACT Admission rate In State Tuition Enrollment Composite -0.6299 -0.3144 0.1980 -0.7141 1.1745 -0.5719 -1.0816 -0.7141 -0.3428 0.1362 0.8697 0.9599 -0.5891 -0.3788 1.3616 0.6555 -0.7315 -0.8294 1.2276 1.1121 -0.7333 0.4581 0.2757 -0.7141 Copyright Cengage Learning. Powered by Cognero.

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Chapter 14 - Data Mining

-0.7590 -0.7245 0.4816 2.6264 -0.3801 0.5116 1.7395 -0.0609 -0.2001 -0.5984 2.7289 -0.5918 -0.6003 -0.4523 -0.5744 -0.3361 0.1629 0.0945 -0.4616 -0.7539

-0.1857 -0.8938 0.9730 0.5224 -0.1213 1.7455 0.2006 0.3937 0.8443 -0.7651 -0.9582 -0.6363 0.5868 0.3937 0.0074 1.1018 -3.3401 1.3593 0.7799 -0.5076

0.4221 0.6351 -1.1366 -1.0328 -1.2463 -1.1742 -1.1098 -1.2463 -1.2463 0.4092 -1.0676 1.3718 0.4018 0.3155 0.5630 0.1133 1.5970 -1.2018 0.7789 1.0029

0.3512 0.1990 -1.6271 0.8077 -1.1706 -0.8662 -0.5619 -1.1706 -1.3228 -0.7141 1.1121 1.5686 0.3512 -0.2575 0.5034 -0.4097 2.4817 -0.7141 0.5034 0.3512

POINTS: 1 DIFFICULTY: Moderate |Bloom's Application QUESTION TYPE: Completion HAS VARIABLES: False PREFACE NAME: Exhibit 14-3 TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/13/2017 11:37 PM DATE MODIFIED: 10/21/2017 10:11 PM 27. Refer to Exhibit 14-3 Choose any three college indices from 1 to 26 as trial values for the cluster centers. Complete the logic to return the name of the college or university associated with the index as well as the standardized numeric measures.

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Chapter 14 - Data Mining ANSWER:

POINTS: 1 DIFFICULTY:Challenging |Bloom's Application QUESTION Completion TYPE: HAS VARIAB False LES: PREFACE N Exhibit 14-3 AME: TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREA 10/13/2017 11:44 PM TED: DATE MODI 10/21/2017 10:11 PM FIED: 28. Refer to Exhibit 14-3 Determine the distances for each college or university to each cluster center.

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Chapter 14 - Data Mining ANSWER:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYP Completion E: HAS VARIABLESFalse : PREFACE NAMEExhibit 14-3 : TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED 10/14/2017 12:14 AM : DATE MODIFIED 10/21/2017 10:11 PM : 29. Refer to Exhibit 14-3 Next determine to which of the trial cluster centers each college or university would be assigned.

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Chapter 14 - Data Mining ANSWER:

POINTS: 1 DIFFICULTY: Challenging |Bloom's Application QUESTION TYPE: Completion HAS VARIABLES: False PREFACE NAME: Exhibit 14-3 TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/14/2017 12:24 AM DATE MODIFIED: 10/21/2017 10:11 PM 30. Refer to Exhibit 14-3 Finally, calculate the minimum total distance to the cluster centers and use Evolutionary Solver to optimize the model. Describe the clusters that are formed.

ANSWER:

The first cluster (centered on IUPUI) seems to be large, public institutions. The second (centered on IUS) seems to be medium, public institutions. The third cluster (centered on U of E) seems to be private institutions.

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Chapter 14 - Data Mining

POINTS: 1 DIFFICULTY: Challenging |Bloom's Analysis QUESTION TYPE: Completion HAS VARIABLES: False PREFACE NAME: Exhibit 14-3 TOPICS: 14.3 Clustering Methods OTHER: BUSPROG - Analytic | DISC Data Mining DATE CREATED: 10/14/2017 12:28 AM DATE MODIFIED: 10/21/2017 10:11 PM

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