Renowned for its clear prose and no-nonsense emphasis on core concepts, Statistics covers fundamentals using real examples to illustrate the techniques. The Fourth Edition has been carefully revised and updated to reflect current data.
New data for the Fourth Edition
Continuing to develop statistical concepts using real data, the Fourth Edition features intriguing examples from medicine, business, genetics, economics, law, psychology, and other fields. Most of the numbers have been updated for the Fourth Edition. There are new results from the 2000 census, the 2004 Gallup Poll, the 2005 Current Population Survey, and more.
Intuitive organization teaches study design early in the text
Statistics, Fourth Edition, introduces controlled experiments and observational studies in the first two chapters, developing the ideas of study design before moving on to descriptive statistics, sampling, and inference.
Classroom-tested problems
Honed by the authors\' teaching experience, the problems in the Fourth Edition test new concepts as they are presented, challenging students to make qualitative judgments and rough estimates as well as numerical calculations. Assumptions underlying the correct use of statistical procedures are explored in detail, as are the consequences of using techniques when assumptions are not satisfied.
Accessible coverage and pedagogy
In clear and direct prose, this classic text conveys statistics as a way of thinking about the world rather than as a set of abstract concepts. Beyond the examples of current interest, there are engaging historical examples to illustrate enduring questions of statistical analysis. Mathematical concepts are integrated with the reading to ensure that students understand the relation between the concepts and the real world. There are many computer graphics to display the data, as well as freehand working drawings. On the lighter side, the Fourth Edition features cartoons by New Yorker artists Dana Fradon and Leo Cullum.
Table of Contents:
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
About the Author :
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.
