Nonparametrics: Statistical Methods Based on Ranks

Rank tests form a class of statistical procedures that have the advantage of great simplicity combined with surprising power. Since their development in the 1940s and 1950s, they have taken their place as strong competitors of the more classical normal theory methods. Rank tests apply only to relatively simple solutions, such as one-, tw0-, and s-sample problems, and testing for independence and randomness, but for these situations they are often the method of choice.

This reprint of a classic reference book describes these tests and the estimating procedures derived from them, and gives an account of their properties. Even though the field of rank tests has undergone little change, important new methodologies have sprung up that also serve the purpose of freeing statistics from the unrealistic model assumptions that so frequently invalidate its applications. All the tests discussed here are now available in a variety of statistical packages.

E.L. Lehmann is Professor of Statistics Emeritus at the University of California, Berkeley. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and the recipient of honorary degrees from the University of Leiden, The Netherlands and the University of Chicago. He is the author of Elements of Large-Sample Theory, Theory of Point Estimation, Second Edition (with George Casella), and Testing Statistical Hypotheses, Third Edition (with Joseph P. Romano).

Lehmann always writes eloquently and his treatment is always authoritative and accurate. However, most of his texts are advanced theoretical books for graduate students in statistics. This one is very different. As he says in his preface, "The purpose of this book is to provide an introduction to nonparametric methods for the analysis and planning of comparative studies." As such he has written it for practitioners. It is filled with illustrative examples of the techniques and intuitive descriptions. There is some mathematics and many exercises at the end of the chapters, but it is intended as a reference text as well as a text for an introductory course. He is very successful in this endeavor.

I have found it very useful over the years and still use it as a reference. In fact, I am sometimes asked as a consultant what procedures are available to test for trends in data. When a nonparametric approach appears warranted, I often refer them to Chapter 7 in this book. It gives a wonderful treatment of tests for independence and provides insight into the tests that are powerful against the alternative hypothesis of a trend over time.


A classic printed and binded like a ... cheap novel   July 8, 2000
H. G. Sung (Houston, TX)
11 out of 13 found this review helpful

This absolute classic is out of print for decades. I was so excited that Prentice Hall reprinted it in 1998 in paperback. It is disturbing that the publisher treated it like a ... cheap novel. This paperback is binded and printed in the worst quality possible that it [may] fall apart in two weeks.