Practical Business Statistics, Seventh Edition, provides a conceptual, realistic, and matter-of-fact approach to managerial statistics that carefully maintains, but does not overemphasize mathematical correctness. The book provides deep understanding of how to learn from data and how to deal with uncertainty while promoting the use of practical computer applications. This valuable, accessible approach teaches present and future managers how to use and understand statistics without an overdose of technical detail, enabling them to better understand the concepts at hand and to interpret results.
The text uses excellent examples with real world data relating to business sector functional areas such as finance, accounting, and marketing. Written in an engaging style, this timely revision is class-tested and designed to help students gain a solid understanding of fundamental statistical principles without bogging them down with excess mathematical details.
1. Part I: Introduction and Descriptive Statistics - p. xix 2. Introduction - p. 1 3. Chapter 1: Introduction: Defining the Role of Statistics in Business - p. 3 4. Chapter 2: Data Structures: Classifying the Various Types of Data Sets - p. 19 5. Chapter 3: Histograms: Looking at the Distribution of Data - p. 41 6. Chapter 4: Landmark Summaries: Interpreting Typical Values and Percentiles - p. 71 7. Chapter 5: Variability: Dealing with Diversity - p. 101 8. Part II: Probability - p. 128 9. Introduction - p. 129 10. Chapter 6: Probability: Understanding Random Situations - p. 131 11. Chapter 7: Random Variables: Working with Uncertain Numbers - p. 163 12. Part III: Statistical Inference - p. 191 13. Introduction - p. 193 14. Chapter 8: Random Sampling: Planning Ahead for Data Gathering - p. 195 15. Chapter 9: Confidence Intervals: Admitting That Estimates Are Not Exact - p. 225 16. Chapter 10: Hypothesis Testing: Deciding Between Reality and Coincidence - p. 255 17. Abstract - p. 255 18. 10.1 Hypotheses Are Not Created Equal! - p. 256 19. 10.2 Testing the Population Mean Against a Known Reference Value: The t-Test - p. 259 20. 10.3 Interpreting a Hypothesis Test - p. 266 21. 10.4 One-Sided Testing - p. 269 22. 10.5 Testing Whether or not a New Observation Comes From the Same Population - p. 275 23. 10.6 Testing Two Samples - p. 276 24. 10.7 End-of-Chapter Materials - p. 283 25. Part IV: Regression and Time Series - p. 295 26. Introduction - p. 297 27. Chapter 11: Correlation and Regression: Measuring and Predicting Relationships - p. 299 28. Abstract - p. 299 29. 11.1 Exploring Relationships Using Scatterplots and Correlations - p. 300 30. 11.2 Regression: Prediction of One Variable From Another - p. 319 31. 11.3 End-of-Chapter Materials - p. 338 32. Chapter 12: Multiple Regression: Predicting One Variable From Several Others - p. 355 33. Abstract - p. 355 34. 12.1 Interpreting the Results of a Multiple Regression - p. 357 35. 12.2 Pitfalls and Problems in Multiple Regression - p. 374 36. 12.3 Dealing With Nonlinear Relationships and Unequal Variability - p. 387 37. 12.4 Indicator Variables: Predicting From Categories - p. 395 38. 12.5 End-of-Chapter Materials - p. 400 39. Chapter 13: Report Writing: Communicating the Results of a Multiple Regression - p. 419 40. Chapter 14: Time Series: Understanding Changes Over Time - p. 431 41. Part V: Methods and Applications - p. 456 42. Introduction - p. 467 43. Chapter 15: ANOVA: Testing for Differences Among Many Samples and Much More - p. 469 44. Chapter 16: Nonparametrics: Testing with Ordinal Data or Nonnormal Distributions - p. 493 45. Chapter 17: Chi-Squared Analysis: Testing for Patterns in Qualitative Data - p. 509 46. Chapter 18: Quality Control: Recognizing and Managing Variation - p. 525 47. Appendix A: Employee Database - p. 547 48. Appendix B: Donations Database - p. 549 49. Appendix C: Self-Test: Solutions to Selected Problems and Database Exercises - p. 553 50. Appendix D: Statistical Tables - p. 567 51. Glossary - p. 601 52. Index - p. 609
Practical Business Statistics, Seventh Edition, provides a conceptual, realistic, and matter-of-fact approach to managerial statistics that carefully maintains, but does not overemphasize mathematical correctness. The book provides deep understanding of how to learn from data and how to deal with uncertainty while promoting the use of practical computer applications. This valuable, accessible approach teaches present and future managers how to use and understand statistics without an overdose of technical detail, enabling them to better understand the concepts at hand and to interpret results.
The text uses excellent examples with real world data relating to business sector functional areas such as finance, accounting, and marketing. Written in an engaging style, this timely revision is class-tested and designed to help students gain a solid understanding of fundamental statistical principles without bogging them down with excess mathematical details.
1. Part I: Introduction and Descriptive Statistics - p. xix 2. Introduction - p. 1 3. Chapter 1: Introduction: Defining the Role of Statistics in Business - p. 3 4. Chapter 2: Data Structures: Classifying the Various Types of Data Sets - p. 19 5. Chapter 3: Histograms: Looking at the Distribution of Data - p. 41 6. Chapter 4: Landmark Summaries: Interpreting Typical Values and Percentiles - p. 71 7. Chapter 5: Variability: Dealing with Diversity - p. 101 8. Part II: Probability - p. 128 9. Introduction - p. 129 10. Chapter 6: Probability: Understanding Random Situations - p. 131 11. Chapter 7: Random Variables: Working with Uncertain Numbers - p. 163 12. Part III: Statistical Inference - p. 191 13. Introduction - p. 193 14. Chapter 8: Random Sampling: Planning Ahead for Data Gathering - p. 195 15. Chapter 9: Confidence Intervals: Admitting That Estimates Are Not Exact - p. 225 16. Chapter 10: Hypothesis Testing: Deciding Between Reality and Coincidence - p. 255 17. Abstract - p. 255 18. 10.1 Hypotheses Are Not Created Equal! - p. 256 19. 10.2 Testing the Population Mean Against a Known Reference Value: The t-Test - p. 259 20. 10.3 Interpreting a Hypothesis Test - p. 266 21. 10.4 One-Sided Testing - p. 269 22. 10.5 Testing Whether or not a New Observation Comes From the Same Population - p. 275 23. 10.6 Testing Two Samples - p. 276 24. 10.7 End-of-Chapter Materials - p. 283 25. Part IV: Regression and Time Series - p. 295 26. Introduction - p. 297 27. Chapter 11: Correlation and Regression: Measuring and Predicting Relationships - p. 299 28. Abstract - p. 299 29. 11.1 Exploring Relationships Using Scatterplots and Correlations - p. 300 30. 11.2 Regression: Prediction of One Variable From Another - p. 319 31. 11.3 End-of-Chapter Materials - p. 338 32. Chapter 12: Multiple Regression: Predicting One Variable From Several Others - p. 355 33. Abstract - p. 355 34. 12.1 Interpreting the Results of a Multiple Regression - p. 357 35. 12.2 Pitfalls and Problems in Multiple Regression - p. 374 36. 12.3 Dealing With Nonlinear Relationships and Unequal Variability - p. 387 37. 12.4 Indicator Variables: Predicting From Categories - p. 395 38. 12.5 End-of-Chapter Materials - p. 400 39. Chapter 13: Report Writing: Communicating the Results of a Multiple Regression - p. 419 40. Chapter 14: Time Series: Understanding Changes Over Time - p. 431 41. Part V: Methods and Applications - p. 456 42. Introduction - p. 467 43. Chapter 15: ANOVA: Testing for Differences Among Many Samples and Much More - p. 469 44. Chapter 16: Nonparametrics: Testing with Ordinal Data or Nonnormal Distributions - p. 493 45. Chapter 17: Chi-Squared Analysis: Testing for Patterns in Qualitative Data - p. 509 46. Chapter 18: Quality Control: Recognizing and Managing Variation - p. 525 47. Appendix A: Employee Database - p. 547 48. Appendix B: Donations Database - p. 549 49. Appendix C: Self-Test: Solutions to Selected Problems and Database Exercises - p. 553 50. Appendix D: Statistical Tables - p. 567 51. Glossary - p. 601 52. Index - p. 609
