Contents:

Summary: Written in clear, everyday language, without the equations that sometimes baffle non-mathematical readers. The goal is teaching students how to think about statistical issues. Techniques are introduced through examples, showing how statistics has helped to solve major problems in political science, psychology, genetics, medicine, and other fields.
Part I. Design of experiments. 1. Controlled experiments -- 2. Observational studies -- Part II. Descriptive statistics. 3. The histogram -- 4. The average and the standard deviation -- 5. The normal approximation for data -- 6. Measurement error -- 7. Plotting points and lines -- Part III. Correlation and regression. 8. Correlation -- 9. More about correlation -- 10. Regression -- 11. The R.M.S. error for regression -- 12. The regression line -- Part IV. Probability. 13. What are the chances? -- 14. More about chance -- 15. The binomial formula -- Part V. Chance variability. 16. The law of averages -- 17. The expected value and standard error -- 18. The normal approximation for probability histograms -- Part VI. Sampling. 19. Sample surveys -- 20. Chance errors in sampling -- 21. The accuracy of percentages -- 22. Measuring employment and unemployment -- 23. The accuracy of averages -- Part VII. Chance models. 24. A model for measurement error -- 25. Chance models in genetics -- Part VIII. Tests of significance. 26. Tests of significance -- 27. More tests for averages -- 28. The chi-square test -- 29. A closer look at tests of significance -- Notes -- Answers to exercises -- Tables.

Item type | Location | Collection | Call number | Status | Date due |
---|---|---|---|---|---|

Books-14days | Bissell Library General Stacks | Non Fiction | 519.5 FRE (Browse shelf) | Available |

Fourth edition first published in United States: New York : W.W. Norton & Co., 2007.

Includes bibliographical references and index.

Part I. Design of experiments. 1. Controlled experiments -- 2. Observational studies -- Part II. Descriptive statistics. 3. The histogram -- 4. The average and the standard deviation -- 5. The normal approximation for data -- 6. Measurement error -- 7. Plotting points and lines -- Part III. Correlation and regression. 8. Correlation -- 9. More about correlation -- 10. Regression -- 11. The R.M.S. error for regression -- 12. The regression line -- Part IV. Probability. 13. What are the chances? -- 14. More about chance -- 15. The binomial formula -- Part V. Chance variability. 16. The law of averages -- 17. The expected value and standard error -- 18. The normal approximation for probability histograms -- Part VI. Sampling. 19. Sample surveys -- 20. Chance errors in sampling -- 21. The accuracy of percentages -- 22. Measuring employment and unemployment -- 23. The accuracy of averages -- Part VII. Chance models. 24. A model for measurement error -- 25. Chance models in genetics -- Part VIII. Tests of significance. 26. Tests of significance -- 27. More tests for averages -- 28. The chi-square test -- 29. A closer look at tests of significance -- Notes -- Answers to exercises -- Tables.

Written in clear, everyday language, without the equations that sometimes baffle non-mathematical readers. The goal is teaching students how to think about statistical issues. Techniques are introduced through examples, showing how statistics has helped to solve major problems in political science, psychology, genetics, medicine, and other fields.