David E. Bock taught mathematics at Ithaca High School for 35 years. He has taught Statistics at Ithaca High School, Tompkins-Cortland Community College, Ithaca College, and Cornell University. Dave has won numerous teaching awards, including the MAA’s Edyth May Sliffe Award for Distinguished High School Mathematics Teaching (twice), Cornell University’s Outstanding Educator Award (three times), and has been a finalist for New York State Teacher of the Year.

Dave holds degrees from the University at Albany in Mathematics (B.A.) and Statistics/Education (M.S.). Dave has been a reader and table leader for the AP Statistics exam and a Statistics consultant to the College Board, leading workshops and institutes for AP Statistics teachers. His understanding of how students learn informs much of this book’s approach.

Floyd Bullard first taught high school math as a Peace Corps volunteer in Benin, West Africa, when he was 23 years old. Today he teaches at the North Carolina School of Science and Mathematics in Durham, North Carolina, where he has been since 1999. Floyd has served on the AP Statistics test development committee and presents regularly at workshops

and conferences for Statistics teachers.

Floyd’s academic degrees are from the Johns Hopkins University (B.S., Applied Mathematics, 1991), the University of North Carolina at Chapel Hill (M.S., Statistics, 1997), and Duke University (Ph.D., Statistics, 2009). He likes to do crossword puzzles and play the piano (not at the same time!).

Paul F. Velleman has an international reputation for innovative Statistics education. He is the author and designer of the multimedia Statistics program ActivStats, for which he was awarded the EDUCOM Medal for innovative uses of computers in teaching Statistics and the ICTCM Award for Innovation in Using Technology in College Mathematics. He also developed the award-winning Statistics program Data Desk and the Internet site Data and Story Library (DASL) (lib.stat.cmu.edu/DASL/), which provides data sets for teaching Statistics. Paul’s understanding of using and teaching with technology informs much of this book’s approach.

Paul taught Statistics at Cornell University in the Department of Statistical Sciences, for which he was awarded the MacIntyre Prize for Exemplary Teaching. He holds an A.B. from Dartmouth College in Mathematics and Social Science, and M.S. and Ph.D. degrees in Statistics from Princeton University, where he studied with John Tukey.

Richard D. De Veaux is an internationally known educator and consultant. He has taught at the Wharton School and the Princeton University School of Engineering, where he won a “Lifetime Award for Dedication and Excellence in Teaching.” Since 1994, he has taught at Williams College. Dick has won both the Wilcoxon and Shewell awards from the American Society for Quality. He is an elected member of the International Statistics Institute (ISI) and a fellow of the American Statistical Association (ASA). Dick is also well known in industry, where for more than 25 years he has consulted for such Fortune 500 companies as American Express, Hewlett-Packard, Alcoa, DuPont, Pillsbury, General Electric, and Chemical Bank. Because he consulted with Mickey Hart on his book Planet Drum , he has also sometimes been called the “Official Statistician for the Grateful Dead.” His real-world experiences and anecdotes illustrate many of this book’s chapters.

Dick holds degrees from Princeton University in Civil Engineering (B.S.E.) and Mathematics (A.B.) and from Stanford University in Dance Education (M.A.) and Statistics (Ph.D.), where he studied dance with Inga Weiss and Statistics with Persi Diaconis.

I. EXPLORING AND UNDERSTANDING DATA

1. Stats Starts Here 

2. Displaying and Describing Categorical Data 

3. Displaying and Summarizing Quantitative Data 

4. Understanding and Comparing Distributions 

5. The Standard Deviation as a Ruler and the Normal Model 

Review of Part I: Exploring and Understanding Data

II. EXPLORING RELATIONSHIPS BETWEEN VARIABLES

6. Scatterplots, Association, and Correlation 

7. Linear Regression 

8. Regression Wisdom 

9. Re-expressing Data: Get It Straight! 

Review of Part II: Exploring Relationships Between Variables

III. GATHERING DATA

10. Understanding Randomness 

11. Sample Surveys 

12. Experiments and Observational Studies 

Review of Part III: Gathering Data

IV. RANDOMNESS AND PROBABILITY

13. From Randomness to Probability 

14. Probability Rules! 

15. Random Variables 

16. Probability Models 

Review of Part IV: Randomness and Probability

V. FROM THE DATA AT HAND TO THE WORLD AT LARGE

17. Sampling Distribution Models 

18. Confidence Intervals for Proportions 

19. Testing Hypotheses About Proportions 

20. More About Tests and Intervals 

21. Comparing Two Proportions 

Review of Part V: From the Data at Hand to the World at Large

VI. LEARNING ABOUT THE WORLD

22. Inferences About Means 

23. Comparing Means 

24. Paired Samples and Blocks 

Review of Part VI: Learning About the World

VII. INFERENCE WHEN VARIABLES ARE RELATED

25. Comparing Counts 

26. Inferences for Regression 

Review of Part VII: Inference When Variables Are Related 

27. Analysis of Variance*–online

28. Multiple Regression*–online

Appendixes:

A. Selected Formulas

B. Guide to Statistical Software 

C. Answers

D. Photo and Text Acknowledgments 

E. Index 

F. Tables 

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