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Test Bank for Quantitative Methods for Business 13th Edition David Anderson

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Test Bank for Quantitative Methods for Business 13th Edition David Anderson

Test Bank for Quantitative Methods for Business 13th Edition David Anderson

Written with the non-mathematician in mind, QUANTITATIVE METHODS FOR BUSINESS, 13E by award-winning authors Anderson, Sweeney, Williams, Camm, Cochran, Fry, and Ohlmann equips your students with a strong conceptual understanding of the critical role that quantitative methods play in today’s decision-making process. This applications-oriented text clearly introduces current quantitative methods, how they work, and how savvy decision makers can most effectively apply and interpret data. A strong managerial orientation motivates learning by weaving relevant, real-world examples throughout. The authors’ hallmark “”Problem-Scenario Approach”” helps readers understand and apply mathematical concepts and techniques. The 13th Edition includes a more holistic description of how variable activity times affect the probability of a project meeting a deadline. In addition, numerous all-new Q.M. in Action vignettes, homework problems, and end-of-chapter cases are included.

Additional ISBNs

1305631536, 1285866312, 0357685644, 1305799259, 9781305631533, 9780357685648, 9781305799257, 9781305449800

Table of Contents

  1. Brief Contents
  2. Contents
  3. Preface
  4. Ch 1: Introduction
  5. Contents
  6. 1.1: Problem Solving and Decision Making
  7. 1.2: Quantitative Analysis and Decision Making
  8. 1.3: Quantitative Analysis
  9. 1.4: Models of Cost, Revenue, and Profit
  10. 1.5: Quantitative Methods in Practice
  11. Summary
  12. Glossary
  13. Problems
  14. Case Problem: Scheduling a Golf League
  15. Ch 2: Introduction to Probability
  16. Contents
  17. 2.1: Experiments and the Sample Space
  18. 2.2: Assigning Probabilities to Experimental Outcomes
  19. 2.3: Events and Their Probabilities
  20. 2.4: Some Basic Relationships of Probability
  21. 2.5: Bayes’ Theorem
  22. 2.6: Simpson’s Paradox
  23. Summary
  24. Glossary
  25. Problems
  26. Case Problem: Hamilton County Judges
  27. Case Problem: College Softball Recruiting
  28. Ch 3: Probability Distributions
  29. Contents
  30. 3.1: Random Variables
  31. 3.2: Discrete Random Variables
  32. 3.3: Binomial Probability Distribution
  33. 3.4: Poisson Probability Distribution
  34. 3.5: Continuous Random Variables
  35. 3.6: Normal Probability Distribution
  36. 3.7: Exponential Probability Distribution
  37. Summary
  38. Glossary
  39. Problems
  40. Case Problem: Specialty Toys
  41. Appendix 3.1: Computing Discrete Probabilities with Excel
  42. Appendix 3.2: Computing Probabilities for Continuous Distributions with Excel
  43. Ch 4: Decision Analysis
  44. Contents
  45. 4.1: Problem Formulation
  46. 4.2: Decision Making without Probabilities
  47. 4.3: Decision Making with Probabilities
  48. 4.4: Risk Analysis and Sensitivity Analysis
  49. 4.5: Decision Analysis with Sample Information
  50. 4.6: Computing Branch Probabilities with Bayes’ Theorem
  51. Summary
  52. Glossary
  53. Problems
  54. Case Problem 1: Property Purchase Strategy
  55. Case Problem 2: Lawsuit Defense Strategy
  56. Appendix 4.1: Using Analytic Solver Platform to Create Decision Trees
  57. Ch 5: Utility and Game Theory
  58. Contents
  59. 5.1: The Meaning of Utility
  60. 5.2: Utility and Decision Making
  61. 5.3: Utility: Other Considerations
  62. 5.4: Introduction to Game Theory
  63. 5.5: Mixed Strategy Games
  64. Summary
  65. Glossary
  66. Problems
  67. Case Problem: Utility, Game Theory, and Product Line Extension Decisions
  68. Ch 6: Time Series Analysis and Forecasting
  69. Contents
  70. 6.1: Time Series Patterns
  71. 6.2: Forecast Accuracy
  72. 6.3: Moving Averages and Exponential Smoothing
  73. 6.4: Linear Trend Projection
  74. 6.5: Seasonality
  75. Summary
  76. Glossary
  77. Problems
  78. Case Problem 1: Forecasting Food and Beverage Sales
  79. Case Problem 2: Forecasting Lost Sales
  80. Appendix 6.1: Forecasting with Excel Data Analysis Tools
  81. Ch 7: Introduction to Linear Programming
  82. Contents
  83. 7.1: A Simple Maximization Problem
  84. 7.2: Graphical Solution Procedure
  85. 7.3: Extreme Points and the Optimal Solution
  86. 7.4: Computer Solution of the RMC Problem
  87. 7.5: A Simple Minimization Problem
  88. 7.6: Special Cases
  89. 7.7: General Linear Programming Notation
  90. Summary
  91. Glossary
  92. Problems
  93. Case Problem 1: Workload Balancing
  94. Case Problem 2: Production Strategy
  95. Case Problem 3: Hart Venture Capital
  96. Appendix 7.1: Solving Linear Programs with Excel Solver
  97. Appendix 7.2: Solving Linear Programs with LINGO
  98. Ch 8: Linear Programming: Sensitivity Analysis and Interpretation of Solution
  99. Contents
  100. 8.1: Introduction to Sensitivity Analysis
  101. 8.2: Objective Function Coefficients
  102. 8.3: Right-Hand Sides
  103. 8.4: Limitations of Classical Sensitivity Analysis
  104. 8.5: More Than Two Decision Variables
  105. 8.6: Electronic Communications Problem
  106. Summary
  107. Glossary
  108. Problems
  109. Case Problem 1: Product Mix
  110. Case Problem 2: Investment Strategy
  111. Case Problem 3: Truck Leasing Strategy
  112. Appendix 8.1: Sensitivity Analysis with Excel Solver
  113. Appendix 8.2: Sensitivity Analysis with LINGO
  114. Ch 9: Linear Programming Applications in Marketing, Finance, and Operations Management
  115. Contents
  116. 9.1: Marketing Applications
  117. 9.2: Financial Applications
  118. 9.3: Operations Management Applications
  119. Summary
  120. Problems
  121. Case Problem 1: Planning an Advertising Campaign
  122. Case Problem 2: Schneider’s Sweet Shop
  123. Case Problem 3: Textile Mill Scheduling
  124. Case Problem 4: Workforce Scheduling
  125. Case Problem 5: Duke Energy Coal Allocation
  126. Appendix 9.1: Excel Solution of Hewlitt Corporation Financial Planning Problem
  127. Ch 10: Distribution and Network Models
  128. Contents
  129. 10.1: Supply Chain Models
  130. 10.2: Assignment Problem
  131. 10.3: Shortest-Route Problem
  132. 10.4: Maximal Flow Problem
  133. 10.5: A Production and Inventory Application
  134. Summary
  135. Glossary
  136. Problems
  137. Case Problem 1: Solutions Plus
  138. Case Problem 2: Supply Chain Design for the Darby Company
  139. Case Problem 3: DK Dental Care
  140. Appendix 10.1: Excel Solver Solution of Transportation, Transshipment, and Assignment Problems
  141. Ch 11: Integer Linear Programming
  142. Contents
  143. 11.1: Types of Integer Linear Programming Models
  144. 11.2: Graphical and Computer Solutions for an All-Integer Linear Program
  145. 11.3: Applications Involving 0-1 Variables
  146. 11.4: Modeling Flexibility Provided by 0-1 Integer Variables
  147. Summary
  148. Glossary
  149. Problems
  150. Case Problem 1: Textbook Publishing
  151. Case Problem 2: Yeager National Bank
  152. Case Problem 3: Production Scheduling with Changeover Costs
  153. Case Problem 4: Applecore Children’s Clothing
  154. Appendix 11.1: Excel Solver Solution of Integer Linear Programs
  155. Appendix 11.2: LINGO Solution of Integer Linear Programs
  156. Ch 12: Advanced Optimization Applications
  157. Contents
  158. 12.1: Data Envelopment Analysis
  159. 12.2: Revenue Management
  160. 12.3: Portfolio Models and Asset Allocation
  161. 12.4: Nonlinear Optimization-The RMC Problem Revisited
  162. 12.5: Constructing an Index Fund
  163. Summary
  164. Glossary
  165. Problems
  166. Case Problem: CAFE Compliance in the Auto Industry
  167. Appendix 12.1: Solving Nonlinear Problems with LINGO
  168. Appendix 12.2: Solving Nonlinear Problems with Excel Solver
  169. Ch 13: Project Scheduling: PERT/CPM
  170. Contents
  171. 13.1: Project Scheduling Based on Expected Activity Times
  172. 13.2: Project Scheduling Considering Uncertain Activity Times
  173. 13.3: Considering Time-Cost Trade-Offs
  174. Summary
  175. Glossary
  176. Problems
  177. Case Problem: R. C. Coleman
  178. Appendix 13.1: Finding Cumulative Probabilities for Normally Distributed Random Variables
  179. Ch 14: Inventory Models
  180. Contents
  181. 14.1: Economic Order Quantity (EOQ) Model
  182. 14.2: Economic Production Lot Size Model
  183. 14.3: Inventory Model with Planned Shortages
  184. 14.4: Quantity Discounts for the EOQ Model
  185. 14.5: Single-Period Inventory Model with Probabilistic Demand
  186. 14.6: Order-Quantity, Reorder Point Model with Probabilistic Demand
  187. 14.7: Periodic Review Model with Probabilistic Demand
  188. Summary
  189. Glossary
  190. Problems
  191. Case Problem 1: Wagner Fabricating Company
  192. Case Problem 2: River City Fire Department
  193. Appendix 14.1: Development of the Optimal Order Quantity (Q*) Formula for the EOQ Model
  194. Appendix 14.2: Development of the Optimal Lot Size (Q*) Formula for the Production Lot Size Model
  195. Ch 15: Waiting Line Models
  196. Contents
  197. 15.1: Structure of a Waiting Line System
  198. 15.2: Single-Server Waiting Line Model with Poisson Arrivals and Exponential Service Times
  199. 15.3: Multiple-Server Waiting Line Model with Poisson Arrivals and Exponential Service Times
  200. 15.4: Some General Relationships for Waiting Line Models
  201. 15.5: Economic Analysis of Waiting Lines
  202. 15.6: Other Waiting Line Models
  203. 15.7: Single-Server Waiting Line Model with Poisson Arrivals and Arbitrary Service Times
  204. 15.8: Multiple-Server Model with Poisson Arrivals, Arbitrary Service Times, and No Waiting Line
  205. 15.9: Waiting Line Models with Finite Calling Populations
  206. Summary
  207. Glossary
  208. Problems
  209. Case Problem 1: Regional Airlines
  210. Case Problem 2: Office Equipment, Inc.
  211. Ch 16: Simulation
  212. Contents
  213. 16.1: What-If Analysis
  214. 16.2: Simulation of Sanotronics Problem
  215. 16.3: Inventory Simulation
  216. 16.4: Waiting Line Simulation
  217. 16.5: Simulation Considerations
  218. Summary
  219. Glossary
  220. Problems
  221. Case Problem 1: Four Corners
  222. Case Problem 2: Harbor Dunes Golf Course
  223. Case Problem 3: County Beverage Drive-Thru
  224. Appendix 16.1: Probability Distributions for Random Variables
  225. Appendix 16.2: Simulation with Analytic Solver Platform
  226. Ch 17: Markov Processes
  227. Contents
  228. 17.1: Market Share Analysis
  229. 17.2: Accounts Receivable Analysis
  230. Summary
  231. Glossary
  232. Problems
  233. Case Problem: Dealer’s Absorbing State Probabilities in Blackjack
  234. Appendix 17.1: Matrix Notation and Operations
  235. Appendix 17.2: Matrix Inversion with Excel
  236. Appendixes
  237. Appendix A: Building Spreadsheet Models
  238. Appendix B: Binomial Probabilities
  239. Appendix C: Poisson Probabilities
  240. Appendix D: Areas for the Standard Normal Distribution
  241. Appendix E: Values of e-y
  242. Appendix F: References and Bibliography
  243. Appendix G: Self-Test Solutions and Answers to Even-Numbered Problems
  244. Index
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Test Bank for Quantitative Methods for Business 13th Edition David Anderson