Statistics for Management and Economics Keller 10th Edition Solutions Manual

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  • ISBN-10 ‏ : ‎ 1285425456
  • ISBN-13 ‏ : ‎ 978-1285425450
  • Author: Gerald Keller

STATISTICS FOR MANAGEMENT AND ECONOMICS, Tenth Edition, emphasizes applications over calculation. It illustrates how vital statistical methods and tools are for today’s managers–and teaches you how to apply them to real business problems. Using a proven three-step “ICI” approach to problem solving, the text teaches you how to IDENTIFY the correct statistical technique by focusing on the problem objective and data type; how to COMPUTE the statistics doing them by hand, using Excel, or using MINITAB; and how to INTERPRET results in the context of the problem. This unique approach enhances your comprehension and practical skills. The text’s vast assortment of data-driven examples, exercises, and cases covers the various functional areas of business, demonstrating the statistical applications that marketing managers, financial analysts, accountants, economists, and others use. These comprehensive applications give you hands-on practice, while solid pedagogical elements make the material more accessible and easy to apply to your world. Completely up-to-date, the tenth edition offers comprehensive coverage, current examples, and Excel 2013 and MINITAB 16 content.

Table Of Contents:

  1. Ch 1: What Is Statistics?
  2. Ch 1: Introduction
  3. 1-1: Key Statistical Concepts
  4. 1-2: Statistical Applications in Business
  5. 1-3: Large Real Data Sets
  6. 1-4: Statistics and the Computer
  7. Ch 1: Chapter Summary
  8. Ch 1: Chapter Exercises
  9. Appendix 1: Instructions for Keller’s Website
  10. Ch 2: Graphical Descriptive Techniques I
  11. Ch 2: Introduction
  12. 2-1: Types of Data and Information
  13. 2-2: Describing a Set of Nominal Data
  14. 2-3: Describing the Relationship between Two Nominal Variables and Comparing Two or More Nominal Dat
  15. Ch 2: Chapter Summary
  16. Ch 2: Chapter Exercises
  17. Ch 3: Graphical Descriptive Techniques II
  18. Ch 3: Introduction
  19. 3-1: Graphical Techniques to Describe a Set of Interval Data
  20. 3-2: Describing Time-Series Data
  21. 3-3: Describing the Relationship between Two Interval Variables
  22. 3-4: Art and Science of Graphical Presentations
  23. Ch 3: Chapter Summary
  24. Ch 3: Chapter Exercises
  25. Ch 4: Numerical Descriptive Techniques
  26. Ch 4: Introduction
  27. Sample Statistic or Population Parameter
  28. 4-1: Measures of Central Location
  29. 4-2: Measures of Variability
  30. 4-3: Measures of Relative Standing and Box Plots
  31. 4-4: Measures of Linear Relationship
  32. 4-5: (Optional) Applications in Professional Sports: Baseball
  33. 4-6: (Optional) Applications in Finance: Market Model
  34. 4-7: Comparing Graphical and Numerical Techniques
  35. 4-8: General Guidelines for Exploring Data
  36. Ch 4: Chapter Summary
  37. Ch 4: Chapter Exercises
  38. Appendix 4: Review of Descriptive Techniques
  39. Ch 5: Data Collection and Sampling
  40. Ch 5: Introduction
  41. 5-1: Methods of Collecting Data
  42. 5-2: Sampling
  43. 5-3: Sampling Plans
  44. 5-4: Sampling and Nonsampling Errors
  45. Ch 5: Chapter Summary
  46. Ch 6: Probability
  47. Ch 6: Introduction
  48. 6-1: Assigning Probability to Events
  49. 6-2: Joint, Marginal, and Conditional Probability
  50. 6-3: Probability Rules and Trees
  51. 6-4: Bayes’s Law
  52. 6-5: Identifying the Correct Method
  53. Ch 6: Chapter Summary
  54. Ch 6: Chapter Exercises
  55. Ch 7: Random Variables and Discrete Probability Distributions
  56. Ch 7: Introduction
  57. 7-1: Random Variables and Probability Distributions
  58. 7-2: Bivariate Distributions
  59. 7-3: (Optional) Applications in Finance: Portfolio Diversification and Asset Allocation
  60. 7-4: Binomial Distribution
  61. 7-5: Poisson Distribution
  62. Ch 7: Chapter Summary
  63. Ch 7: Chapter Exercises
  64. Ch 8: Continuous Probability Distributions
  65. Ch 8: Introduction
  66. 8-1: Probability Density Functions
  67. 8-2: Normal Distribution
  68. 8-3: (Optional) Exponential Distribution
  69. 8-4: Other Continuous Distributions
  70. Ch 8: Chapter Summary
  71. Ch 9: Sampling Distributions
  72. Ch 9: Introduction
  73. 9-1: Sampling Distribution of the Mean
  74. 9-2: Sampling Distribution of a Proportion
  75. 9-3: Sampling Distribution of the Difference between Two Means
  76. 9-4: From Here to Inference
  77. Ch 9: Chapter Summary
  78. Ch 10: Introduction to Estimation
  79. Ch 10: Introduction
  80. 10-1: Concepts of Estimation
  81. 10-2: Estimating the Population Mean When the Population Standard Deviation Is Known
  82. 10-3: Selecting the Sample Size
  83. Ch 10: Chapter Summary
  84. Ch 11: Introduction to Hypothesis Testing
  85. Ch 11: Introduction
  86. 11-1: Concepts of Hypothesis Testing
  87. 11-2: Testing the Population Mean When the Population Standard Deviation Is Known
  88. 11-3: Calculating the Probability of a Type II Error
  89. 11-4: The Road Ahead
  90. Ch 11: Chapter Summary
  91. Ch 12: Inference about a Population
  92. Ch 12: Introduction
  93. 12-1: Inference about a Population Mean When the Standard Deviation Is Unknown
  94. 12-2: Inference about a Population Variance
  95. 12-3: Inference about a Population Proportion
  96. 12-4: (Optional) Applications in Marketing: Market Segmentation
  97. Ch 12: Chapter Summary
  98. Ch 12: Chapter Exercises
  99. Ch 13: Inference about Comparing Two Populations
  100. Ch 13: Introduction
  101. 13-1: Inference about the Difference between Two Means: Independent Samples
  102. 13-2: Observational and Experimental Data
  103. 13-3: Inference about the Difference between Two Means: Matched Pairs Experiment
  104. 13-4: Inference about the Ratio of Two Variances
  105. 13-5: Inference about the Difference between Two Population Proportions
  106. Ch 13: Chapter Summary
  107. Ch 13: Chapter Exercises
  108. Appendix 13: Review of Chapters 12 and 13
  109. Ch 14: Analysis of Variance
  110. Ch 14: Introduction
  111. 14-1: One-Way Analysis of Variance
  112. 14-2: Multiple Comparisons
  113. 14-3: Analysis of Variance Experimental Designs
  114. 14-4: Randomized Block (Two-Way) Analysis of Variance
  115. 14-5: Two-Factor Analysis of Variance
  116. 14-6: (Optional) Applications in Operations Management: Finding and Reducing Variation
  117. Ch 14: Chapter Summary
  118. Ch 14: Chapter Exercises
  119. Appendix 14: Review of Chapters 12 to 14
  120. Ch 15: Chi-Squared Tests
  121. Ch 15: Introduction
  122. 15-1: Chi-Squared Goodness-of-Fit Test
  123. 15-2: Chi-Squared Test of a Contingency Table
  124. 15-3: Summary of Tests on Nominal Data
  125. 15-4: (Optional) Chi-Squared Test for Normality
  126. Ch 15: Chapter Summary
  127. Ch 15: Chapter Exercises
  128. Appendix 15: Review of Chapters 12 to 15
  129. Ch 16: Simple Linear Regression and Correlation
  130. Ch 16: Introduction
  131. 16-1: Model
  132. 16-2: Estimating the Coefficients
  133. 16-3: Error Variable: Required Conditions
  134. 16-4: Assessing the Model
  135. 16-5: Using the Regression Equation
  136. 16-6: Regression Diagnostics—I
  137. Ch 16: Chapter Summary
  138. Ch 16: Chapter Exercises
  139. Appendix 16: Review of Chapters 12 to 16
  140. Ch 17: Multiple Regression
  141. Ch 17: Introduction
  142. 17-1: Model and Required Conditions
  143. 17-2: Estimating the Coefficients and Assessing the Model
  144. 17-3: Regression Diagnostics—II
  145. 17-4: Regression Diagnostics—III (Time Series)
  146. Ch 17: Chapter Summary
  147. Ch 17: Chapter Exercises
  148. Appendix 17: Review of Chapters 12 to 17
  149. Ch 18: Model Building
  150. Ch 18: Introduction
  151. 18-1: Polynomial Models
  152. 18-2: Nominal Independent Variables
  153. 18-3: (Optional) Applications in Human Resources Management: Pay Equity
  154. 18-4: (Optional) Stepwise Regression
  155. 18-5: Model Building
  156. Ch 18: Chapter Summary
  157. Ch 18: Chapter Exercises
  158. Ch 19: Nonparametric Statistics
  159. Ch 19: Introduction
  160. 19-1: Wilcoxon Rank Sum Test
  161. 19-2: Sign Test and Wilcoxon Signed Rank Sum Test
  162. 19-3: Kruskal–Wallis Test and Friedman Test
  163. 19-4: Spearman Rank Correlation Coefficient
  164. Ch 19: Chapter Summary
  165. Ch 19: Chapter Exercises
  166. Appendix 19: Review of Statistical Inference (Chapters 12 to 19)
  167. Ch 20: Time-Series Analysis and Forecasting
  168. Ch 20: Introduction
  169. 20-1: Time-Series Components
  170. 20-2: Smoothing Techniques
  171. 20-3: Trend and Seasonal Effects
  172. 20-4: Introduction to Forecasting
  173. 20-5: Forecasting Models
  174. Ch 20: Chapter Summary
  175. Ch 21: Statistical Process Control
  176. Ch 21: Introduction
  177. 21-1: Process Variation
  178. 21-2: Control Charts
  179. 21-3: Control Charts for Variables: X and S Charts
  180. 21-4: Control Charts for Attributes: P Chart
  181. Ch 21: Chapter Summary
  182. Ch 22: Decision Analysis
  183. Ch 22: Introduction
  184. 22-1: Decision Problem
  185. 22-2: Acquiring, Using, and Evaluating Additional Information

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