Preface
Index of Applications
Part I. Exploring and Collecting Data
Chapter 1. Data and Decisions (H&M)
Chapter 2. Visualizing and Describing Categorical Data (Dalia Research)
Chapter 3. Describing, Displaying, and Visualizing Quantitative Data (AIG)
Chapter 4. Correlation and Linear Regression (Zillow.com)
Part II. Modeling with Probability
Chapter 5. Randomness and Probability (Credit Reports, the Fair Isaacs Corporation, and Equifax)
Chapter 6. Random Variables and Probability Models (Metropolitan Life Insurance Company)
Chapter 7. The Normal and Other Continuous Distributions (The NYSE)
Part III. Gathering Data
Chapter 8. Data Sources: Observational Studies and Surveys (Roper Polls)
Chapter 9. Data Sources: Experiments (Capital One)
Part IV. Inference for Decision Making
Chapter 10. Sampling Distributions and Confidence Intervals for Proportions (Marketing Credit Cards: The MBNA Story)
Chapter 11. Confidence Intervals for Means (Guinness & Co.)
Chapter 12. Testing Hypotheses (Casting Ingots)
Chapter 13. More About Tests and Intervals (Travelers Insurance)
Chapter 14. Comparing Two Means (Visa Global Organization)
Chapter 15. Inference for Counts: Chi-Square Tests (SAC Capital)
Part V. Models for Decision Making
Chapter 16. Inference for Regression (Nambé Mills)
Chapter 17. Understanding Residuals (Kelloggs)
Chapter 18. Multiple Regression (Zillow.com)
Chapter 19. Building Multiple Regression Models (Bolliger and Mabillard)
Chapter 20. Time Series Analysis (Whole Foods Market®)
Part VI. Analytics
Chapter 21. Introduction to Big Data and Data Mining (Paralyzed Veterans of America)
Part VII
Chapter 22. Quality Control (Sony)
Chapter 23. Nonparametric Methods (i4cp)
Chapter 24. Decision Making and Risk (Data Description, inc.)
Chapter 25. Analysis of Experiments and Observational Studies
Appendix A. Answers
Appendix B. Tables and Selected Formulas
Appendix C. Photo Acknowledgments

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