Nonparametric Statistical Methods, 2nd Edition

Rating:
Summary: A SUPERB Introduction- bound to be a Stat Classic
Review: I found this book to be very helpful and it required minimal interpretation from academia to understand. More so for the practicioner than the theoretician.

Rating:
Summary: revision of classical on nonparametric methods
Review: In the 1970s this text became a classic on the subject of nonparametric methods. It was written for practitioners and students. It is introductory and comprehensive. It describes the methods accurately but does not cover the theory. Later Randles and Wolfe wrote a companion book covering the theory. This revision is much larger and covers the many advances over the past 20 years. It covers bootstrap methods as well. Also computational advances are discussed.

Conover's "Practical Nonparametric Statistics" is another fine book for practitioners. I also recommend Lehmann's book on nonparametrics. It was published in 1975 and is not easy to find these days.

Rating:
Summary: An excellent, encyclopediac approach
Review: This is an excellent book on a somewhat underutilized group of statistical techniques. It could be used for a course in nonparametric statistics at the graduate level in Psychology or the social sciences, although I don't think the whole book could be covered in a semester.

It is perhaps more valuable as a reference for the practicing data analyst. Because of the format, it is relatively easy to find a procedure that does what you want. There are 11 chapters, the first of which is an introduction, and the others each cover one type of problem (e.g. the one-sample location problem). Within each chapter are a variety of procedures, each of which is discussed in the same format: Procedure, large-sample approximation, ties, example, comments, properties and problems.

In addition, there are close to 200 pages of tables, many of which I haven't seen elsewhere.

Overall, highly recommended for anyone who needs to use or teach these techniques.