Statistics

David Freedman received his B.Sc. from McGill and his Ph.D. from Princeton. He has worked as a consultant for the City of San Francisco, the County of Los Angeles, the U.S. Department of Energy, and the U.S. Department of Justice. He has written several previous books and numerous technical papers. He is a member of the American Academy of Arts and Sciences and teaches at the University of California, Berkeley. Robert Pisani received his B.A. and Ph.D. at the University of California, Berkeley. His research interests include probability models of market-price behavior and the statistical valuation of financial instruments. Roger Purves received his B.A. at the University of British Columbia and his Ph.D. at the University of California, Berkeley, where he currently teaches. His research interests are in the mathematical foundations of probability theory.

PART I. DESIGNS OF EXPERIMENTS Chapter 1. Controlled Experiments Chapter 2. Observational Studies PART II. DESCRIPTIVE STATISTICS Chapter 3. The Histogram Chapter 4. The Average Standard Deviation Chapter 5. The Normal Approximation for Data Chapter 6. Measurement Error Chapter 7. Plotting Points and Lines PART III. CORRELATION AND REGRESSION Chapter 8. Correlation Chapter 9. More about Correlation Chapter 10. Regression Chapter 11. The R.M.S. Error for Regression Chapter 12. The Regression Line PART IV. PROBABILITY Chapter 13. What Are the Chances Chapter 14. More about Chance Chapter 15. The Binomial Formula PART V. CHANCE VARIABILITY Chapter 16. The Law of Averages Chapter 17. The Expected Value and Standard Error Chapter 18. The Normal Approximation for Probablity PART VI. SAMPLING Chapter 19. Sample Surveys Chapter 20. Chance Errors in Sampling Chapter 21. The Accuracy of Percentages Chapter 22. Measuring Employment and Significance Unemployment Chapter 23. The Accuracy of Averages PART VII. CHANCE MODELS Chapter 24. Model for Measurement Error Chapter 25. Chance Models in Genetics PART VIII. TESTS OF SIGNIFICANCE Chapter 26. Tests of Significance Chapter 27 More Tests for Averages Chapter 28. The Chi-Square Test Chapter 29. A Closer Look at Tests of Significance