Covers the most commonly used nonparametric procedures
States the assumptions, develops the theory behind the methods, and illustrates the techniques using realistic examples from the social, behavioural, 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
Nonparametric Statistical Inference, Sixth Edition, has been thoroughly revised and rewritten to make it more readable and reader-friendly. All R solutions are new and make this book much more useful for applications in modern times. It has been updated and contains 100 unique citations, including some of the most recent, to make it more current and valuable for researchers.