Includes bibliographical references and index.

1. Introduction and Fundamentals
2. Order Statistics, Quantiles, and Coverages
3. Tests of Randomness
4. Tests of Goodness of Fit
5. One-Sample and Paired-Sample Procedures
6. The General Two-Sample Problem
7. Linear Rank Statistics and the General Two-Sample Problem
8. Linear Rank Tests for the Location Problem
9. Linear Rank Tests for the Scale Problem
10. Tests of the Equality of k Distributions
11. Measures of Association for Bivariate Samples
12. Measures of Association in Multiple Classifications
13. Asymptotic Relative Efficiency
14. Analysis of Count Data
15. Summary

"Nonparametric Statistical Inference, Sixth Edition has been thoroughly revised and rewritten to make it more readable and reader-friendly. All of the R solutions are new and make this book much more useful for applications in the modern times. It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers. · Covers the most commonly used nonparametric procedures. · States the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences. · Presents tests of hypotheses, confidence interval estimation, sample size determination, power, and comparisons of competing procedures. · Includes an Appendix of user-friendly tables needed for solutions to all data- oriented examples. · Gives examples of computer applications based on R, MINITAB, STATXACT, and SAS. Lists over 100 new references"--

English