The Basic Practice of Statistics

David S. Moore is Shanti S. Gupta Distinguished Professor of Statistics, Emeritus, at Purdue University. He is an elected fellow of the American Statistical Association and of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He is the author of influential articles on statistics education and of several leading texts. William I. Notz is Professor of Statistics at the Ohio State University. His first academic job was as an assistant professor in the Department of Statistics at Purdue University. While there, he taught the introductory concepts course with Professor Moore and as a result of this experience he developed an interest in statistical education. Michael A. Fligner is an Adjunct Professor at the University of California at Santa Cruz and a non-resident Professor Emeritus with the Ohio State University. Professor Fligner is currently associated with the Center for Statistical Analysis in the Social Sciences at the University of California at Santa Cruz.

PART I: EXPLORING DATA.- 0. Getting Started.- 1. Picturing Distributions with Graphs.- 2. Describing Distributions with Numbers.- 3. The Normal Distributions.- 4. Scatterplots and Correlation.- 5. Regression.- 6. Two-Way Tables*.- 7. Exploring Data: Part I Review. PART II: PRODUCING DATA. 8. Producing Data: Sampling.- 9. Producing Data: Experiments.- 10. Data Ethics*.- 11. Producing Data: Part II Review. PART III: FROM DATA PRODUCTION TO INFERENCE. 12. Introducing Probability.- 13. General Rules of Probability*.- 14. Binomial Distributions*.- 15. Sampling Distributions.- 16. Confidence Intervals: The Basics.- 17. Tests of Significance: The Basics.- 18. Inference in Practice.- 19. From Data Production to Inference: Part III Review. PART IV: INFERENCE ABOUT VARIABLES. 20. Inference about a Population Mean.- 21. Comparing Two Means.- 22. Inference about a Population Proportion.- 23. Comparing Two Proportions.- 24. Inference about Variables: Part IV Review. PART V: INFERENCE ABOUT RELATIONSHIPS. 25. Two Categorical Variables: The Chi-Square Test.- 26. Inference for Regression.- 27. One-Way Analysis of Variance: Comparing Several Means. PART VI: OPTIONAL COMPANION CHAPTERS(available online). 28. Nonparametric Tests.- 29. Multiple Regression.- 30. More about Analysis of Variance.- 31. Statistical Process Control.- 32. Resampling: Permutation Tests and the Bootstrap.