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Solution Manual for Introduction to Business Statistics, 7th Edition

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Solution Manual for Introduction to Business Statistics, 7th Edition

Product details:

  • ISBN-10 ‏ : ‎ 053845217X
  • ISBN-13 ‏ : ‎ 978-0538452175
  • Author: Dr. Ron Weiers

Highly praised for its exceptional clarity, technical accuracy, and useful examples, Weiers’ INTRODUCTION TO BUSINESS STATISTICS, Seventh Edition, introduces fundamental statistical concepts with an engaging, conversational presentation and a strong emphasis on the practical relevance of course material to students’ lives and careers. The text’s outstanding illustrations, friendly language, non-technical terminology, and current examples involving real-world business and personal settings will capture students’ interest and prepare them for success from day one. Continuing cases, contemporary business applications, and more than 300 new or revised exercises and problems reflect important trends and the latest developments in today’s dynamic business environment — all with an accuracy you and your students can trust.

Table contents:

  1. CHAPTER 1: A Preview of Business Statistics
  2. 1.1: INTRODUCTION
  3. 1.2: STATISTICS: YESTERDAY AND TODAY
  4. 1.3: DESCRIPTIVE VERSUS INFERENTIAL STATISTICS
  5. 1.4: TYPES OF VARIABLES AND SCALES OF MEASUREMENT
  6. 1.5: STATISTICS IN BUSINESS DECISIONS
  7. 1.6: BUSINESS STATISTICS: TOOLS VERSUS TRICKS
  8. 1.7: SUMMARY
  9. STATISTICS IN ACTION
  10. CHAPTER EXERCISES
  11. CHAPTER 2: Visual Description of Data
  12. 2.1: INTRODUCTION
  13. 2.2: THE FREQUENCY DISTRIBUTION AND THE HISTOGRAM
  14. 2.3: THE STEM-AND-LEAF DISPLAY AND THE DOTPLOT
  15. 2.4: OTHER METHODS FOR VISUAL REPRESENTATION OF THE DATA
  16. 2.5: THE SCATTER DIAGRAM
  17. 2.6: TABULATION, CONTINGENCY TABLES, AND THE EXCEL PivotTable
  18. 2.7: SUMMARY
  19. EQUATIONS
  20. CHAPTER EXERCISES
  21. INTEGRATED CASES
  22. CHAPTER 3: Statistical Description of Data
  23. 3.1: INTRODUCTION
  24. 3.2: STATISTICAL DESCRIPTION: MEASURES OF CENTRAL TENDENCY
  25. 3.3: STATISTICAL DESCRIPTION: MEASURES OF DISPERSION
  26. 3.4: ADDITIONAL DISPERSION TOPICS
  27. 3.5: DESCRIPTIVE STATISTICS FROM GROUPED DATA
  28. 3.6: STATISTICAL MEASURES OF ASSOCIATION
  29. 3.7: SUMMARY
  30. EQUATIONS
  31. CHAPTER EXERCISES
  32. INTEGRATED CASES
  33. BUSINESS CASE
  34. SEEING STATISTICS: APPLET 1
  35. SEEING STATISTICS: APPLET 2
  36. CHAPTER 4: Data Collection and Sampling Methods
  37. 4.1: INTRODUCTION
  38. 4.2: RESEARCH BASICS
  39. 4.3: SURVEY RESEARCH
  40. 4.4: EXPERIMENTATION AND OBSERVATIONAL RESEARCH
  41. 4.5: SECONDARY DATA
  42. 4.6: THE BASICS OF SAMPLING
  43. 4.7: SAMPLING METHODS
  44. 4.8: SUMMARY
  45. CHAPTER EXERCISES
  46. INTEGRATED CASE
  47. SEEING STATISTICS: APPLET 3
  48. CHAPTER 5: Probability: Review of Basic Concepts
  49. 5.1: INTRODUCTION
  50. 5.2: PROBABILITY: TERMS AND APPROACHES
  51. 5.3: UNIONS AND INTERSECTIONS OF EVENTS
  52. 5.4: ADDITION RULES FOR PROBABILITY
  53. 5.5: MULTIPLICATION RULES FOR PROBABILITY
  54. 5.6: BAYES’ THEOREM AND THE REVISION OF PROBABILITIES
  55. 5.7: COUNTING: PERMUTATIONS AND COMBINATIONS
  56. 5.8: SUMMARY
  57. EQUATIONS
  58. CHAPTER EXERCISES
  59. INTEGRATED CASES
  60. BUSINESS CASE
  61. CHAPTER 6: Discrete Probability Distributions
  62. 6.1: INTRODUCTION
  63. 6.2: THE BINOMIAL DISTRIBUTION
  64. 6.3: THE HYPERGEOMETRIC DISTRIBUTION
  65. 6.4: THE POISSON DISTRIBUTION
  66. 6.5: SIMULATING OBSERVATIONS FROM A DISCRETE PROBABILITY DISTRIBUTION
  67. 6.6: SUMMARY
  68. EQUATIONS
  69. CHAPTER EXERCISES
  70. INTEGRATED CASE
  71. CHAPTER 7: Continuous Probability Distributions
  72. 7.1: INTRODUCTION
  73. 7.2: THE NORMAL DISTRIBUTION
  74. 7.3: THE STANDARD NORMAL DISTRIBUTION
  75. 7.4: THE NORMAL APPROXIMATION TO THE BINOMIAL DISTRIBUTION
  76. 7.5: THE EXPONENTIAL DISTRIBUTION
  77. 7.6: SIMULATING OBSERVATIONS FROM A CONTINUOUS PROBABILITY DISTRIBUTION
  78. 7.7: SUMMARY
  79. EQUATIONS
  80. CHAPTER EXERCISES
  81. INTEGRATED CASES
  82. SEEING STATISTICS: APPLET 4
  83. SEEING STATISTICS: APPLET 5
  84. SEEING STATISTICS: APPLET 6
  85. CHAPTER 8: Sampling Distributions
  86. 8.1: INTRODUCTION
  87. 8.2: A PREVIEW OF SAMPLING DISTRIBUTIONS
  88. 8.3: THE SAMPLING DISTRIBUTION OF THE MEAN
  89. 8.4: THE SAMPLING DISTRIBUTION OF THE PROPORTION
  90. 8.5: SAMPLING DISTRIBUTIONS WHEN THE POPULATION IS FINITE
  91. 8.6: COMPUTER SIMULATION OF SAMPLING DISTRIBUTIONS
  92. 8.7: SUMMARY
  93. EQUATIONS
  94. CHAPTER EXERCISES
  95. INTEGRATED CASE
  96. SEEING STATISTICS: APPLET 7
  97. SEEING STATISTICS: APPLET 8
  98. CHAPTER 9: Estimation from Sample Data
  99. 9.1: INTRODUCTION
  100. 9.2: POINT ESTIMATES
  101. 9.3: A PREVIEW OF INTERVAL ESTIMATES
  102. 9.4: CONFIDENCE INTERVAL ESTIMATES FOR THE MEAN: σ KNOWN
  103. 9.5: CONFIDENCE INTERVAL ESTIMATES FOR THE MEAN: σ UNKNOWN
  104. 9.6: CONFIDENCE INTERVAL ESTIMATES FOR THE POPULATION PROPORTION
  105. 9.7: SAMPLE SIZE DETERMINATION
  106. 9.8: WHEN THE POPULATION IS FINITE
  107. 9.9: SUMMARY
  108. EQUATIONS
  109. CHAPTER EXERCISES
  110. INTEGRATED CASES
  111. SEEING STATISTICS: APPLET 9
  112. SEEING STATISTICS: APPLET 10
  113. SEEING STATISTICS: APPLET 11
  114. CHAPTER 10: Hypothesis Tests Involving a Sample Mean or Proportion
  115. 10.1: INTRODUCTION
  116. 10.2: HYPOTHESIS TESTING: BASIC PROCEDURES
  117. 10.3: TESTING A MEAN, POPULATION STANDARD DEVIATION KNOWN
  118. 10.4: CONFIDENCE INTERVALS AND HYPOTHESIS TESTING
  119. 10.5: TESTING A MEAN, POPULATION STANDARD DEVIATION UNKNOWN
  120. 10.6: TESTING A PROPORTION
  121. 10.7: THE POWER OF A HYPOTHESIS TEST
  122. 10.8: SUMMARY
  123. EQUATIONS
  124. CHAPTER EXERCISES
  125. INTEGRATED CASES
  126. BUSINESS CASE
  127. SEEING STATISTICS: APPLET 12
  128. SEEING STATISTICS: APPLET 13
  129. CHAPTER 11: Hypothesis Tests Involving Two Sample Means or Proportions
  130. 11.1: INTRODUCTION
  131. 11.2: THE POOLED-VARIANCES t-TEST FOR COMPARING THE MEANS OF TWO INDEPENDENT SAMPLES
  132. 11.3: THE UNEQUAL-VARIANCES t-TEST FOR COMPARING THE MEANS OF TWO INDEPENDENT SAMPLES
  133. 11.4: THE z-TEST FOR COMPARING THE MEANS OF TWO INDEPENDENT SAMPLES
  134. 11.5: COMPARING TWO MEANS WHEN THE SAMPLES ARE DEPENDENT
  135. 11.6: COMPARING TWO SAMPLE PROPORTIONS
  136. 11.7: COMPARING THE VARIANCES OF TWO INDEPENDENT SAMPLES
  137. 11.8: SUMMARY
  138. EQUATIONS
  139. CHAPTER EXERCISES
  140. INTEGRATED CASES
  141. BUSINESS CASE
  142. SEEING STATISTICS: APPLET 14
  143. CHAPTER 12: Analysis of Variance Tests
  144. 12.1: INTRODUCTION
  145. 12.2: ANALYSIS OF VARIANCE: BASIC CONCEPTS
  146. 12.3: ONE-WAY ANALYSIS OF VARIANCE
  147. 12.4: THE RANDOMIZED BLOCK DESIGN
  148. 12.5: TWO-WAY ANALYSIS OF VARIANCE
  149. 12.6: SUMMARY
  150. EQUATIONS
  151. CHAPTER EXERCISES
  152. INTEGRATED CASES
  153. BUSINESS CASE
  154. SEEING STATISTICS: APPLET 15
  155. SEEING STATISTICS: APPLET 16
  156. CHAPTER 13: Chi-Square Applications
  157. 13.1: INTRODUCTION
  158. 13.2: BASIC CONCEPTS IN CHI-SQUARE TESTING
  159. 13.3: TESTS FOR GOODNESS OF FIT AND NORMALITY
  160. 13.4: TESTING THE INDEPENDENCE OF TWO VARIABLES
  161. 13.5: COMPARING PROPORTIONS FROM k INDEPENDENT SAMPLES
  162. 13.6: ESTIMATION AND TESTS REGARDING THE POPULATION VARIANCE
  163. 13.7: SUMMARY
  164. EQUATIONS
  165. CHAPTER EXERCISES
  166. INTEGRATED CASES
  167. BUSINESS CASE
  168. SEEING STATISTICS: APPLET 17
  169. CHAPTER 14: Nonparametric Methods
  170. 14.1: INTRODUCTION
  171. 14.2: WILCOXON SIGNED RANK TEST FOR ONE SAMPLE
  172. 14.3: WILCOXON SIGNED RANK TEST FOR COMPARING PAIRED SAMPLES
  173. 14.4: WILCOXON RANK SUM TEST FOR COMPARING TWO INDEPENDENT SAMPLES
  174. 14.5: KRUSKAL-WALLIS TEST FOR COMPARING MORE THAN TWO INDEPENDENT SAMPLES
  175. 14.6: FRIEDMAN TEST FOR THE RANDOMIZED BLOCK DESIGN
  176. 14.7: OTHER NONPARAMETRIC METHODS
  177. 14.8: SUMMARY
  178. EQUATIONS
  179. CHAPTER EXERCISES
  180. INTEGRATED CASE
  181. BUSINESS CASE
  182. CHAPTER 15: Simple Linear Regression and Correlation
  183. 15.1: INTRODUCTION
  184. 15.2: THE SIMPLE LINEAR REGRESSION MODEL
  185. 15.3: INTERVAL ESTIMATION USING THE SAMPLE REGRESSION LINE
  186. 15.4: CORRELATION ANALYSIS
  187. 15.5: ESTIMATION AND TESTS REGARDING THE SAMPLE REGRESSION LINE
  188. 15.6: ADDITIONAL TOPICS IN REGRESSION AND CORRELATION ANALYSIS
  189. 15.7: SUMMARY
  190. EQUATIONS
  191. CHAPTER EXERCISES
  192. INTEGRATED CASES
  193. BUSINESS CASE
  194. SEEING STATISTICS: APPLET 18
  195. SEEING STATISTICS: APPLET 19
  196. SEEING STATISTICS: APPLET 20
  197. CHAPTER 16: Multiple Regression and Correlation
  198. 16.1: INTRODUCTION
  199. 16.2: THE MULTIPLE REGRESSION MODEL
  200. 16.3: INTERVAL ESTIMATION IN MULTIPLE REGRESSION
  201. 16.4: MULTIPLE CORRELATION ANALYSIS
  202. 16.5: SIGNIFICANCE TESTS IN MULTIPLE REGRESSION AND CORRELATION
  203. 16.6: OVERVIEW OF THE COMPUTER ANALYSIS AND INTERPRETATION
  204. 16.7: ADDITIONAL TOPICS IN MULTIPLE REGRESSION AND CORRELATION
  205. 16.8: SUMMARY
  206. EQUATIONS
  207. CHAPTER EXERCISES
  208. INTEGRATED CASES
  209. BUSINESS CASE
  210. CHAPTER 17: Model Building
  211. 17.1: INTRODUCTION
  212. 17.2: POLYNOMIAL MODELS WITH ONE QUANTITATIVE PREDICTOR VARIABLE
  213. 17.3: POLYNOMIAL MODELS WITH TWO QUANTITATIVE PREDICTOR VARIABLES
  214. 17.4: QUALITATIVE VARIABLES
  215. 17.5: DATA TRANSFORMATIONS
  216. 17.6: MULTICOLLINEARITY
  217. 17.7: STEPWISE REGRESSION
  218. 17.8: SELECTING A MODEL
  219. 17.9: SUMMARY
  220. EQUATIONS
  221. CHAPTER EXERCISES
  222. INTEGRATED CASES
  223. BUSINESS CASE
  224. CHAPTER 18: Models for Time Series and Forecasting
  225. 18.1: INTRODUCTION
  226. 18.2: TIME SERIES
  227. 18.3: SMOOTHING TECHNIQUES
  228. 18.4: SEASONAL INDEXES
  229. 18.5: FORECASTING
  230. 18.6: EVALUATING ALTERNATIVE MODELS: MAD AND MSE
  231. 18.7: AUTOCORRELATION, THE DURBIN-WATSON TEST, AND AUTOREGRESSIVE FORECASTING
  232. 18.8: INDEX NUMBERS
  233. 18.9: SUMMARY
  234. EQUATIONS
  235. CHAPTER EXERCISES
  236. INTEGRATED CASE
  237. CHAPTER 19: Decision Theory
  238. 19.1: INTRODUCTION
  239. 19.2: STRUCTURING THE DECISION SITUATION
  240. 19.3: NON-BAYESIAN DECISION MAKING
  241. 19.4: BAYESIAN DECISION MAKING
  242. 19.5: THE OPPORTUNITY LOSS APPROACH
  243. 19.6: INCREMENTAL ANALYSIS AND INVENTORY DECISIONS
  244. 19.7: SUMMARY
  245. EQUATIONS
  246. CHAPTER EXERCISES
  247. INTEGRATED CASE
  248. CHAPTER 20: Total Quality Management
  249. 20.1: INTRODUCTION
  250. 20.2: A HISTORICAL PERSPECTIVE AND DEFECT DETECTION
  251. 20.3: THE EMERGENCE OF TOTAL QUALITY MANAGEMENT
  252. 20.4: PRACTICING TOTAL QUALITY MANAGEMENT
  253. 20.5: SOME STATISTICAL TOOLS FOR TOTAL QUALITY MANAGEMENT
  254. 20.6: STATISTICAL PROCESS CONTROL: THE CONCEPTS
  255. 20.7: CONTROL CHARTS FOR VARIABLES
  256. 20.8: CONTROL CHARTS FOR ATTRIBUTES
  257. 20.9: ADDITIONAL STATISTICAL PROCESS CONTROL AND QUALITY MANAGEMENT TOPICS
  258. 20.10: SUMMARY
  259. EQUATIONS
  260. CHAPTER EXERCISES
  261. INTEGRATED CASES
  262. SEEING STATISTICS: APPLET 21
  263. APPENDIX A: STATISTICAL TABLES
  264. APPENDIX B: SELECTED ANSWERS
  265. INDEX/GLOSSARY

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