Customer Reviews

Handbook of Parametric and Nonparametric Statistical Procedures: Third Edition

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From a student's point of view, this book contains numerous aids to assist in understanding the application of many statistical tests. For example, the decision charts on pages 27-30 help to determine what tests are applicable for analysis given the type of data the researcher plans to obtain in the study. I might decide that the use of the Kruskal-Wallis is appropriate. The chart refers me to Test 17, which is on page 396. I can go to that page, and get a complete plain-language explanation of the test and what it measures. Examples are provided for each test to determine appropriateness, and this section is followed by an example with computations. A complete analysis of the data and a discussion of the test ensues. All of the necessary tables for computation are included in appendices. I am a complete novice at statistics, and this book has helped me to understand material in classroom lectures.

This is an excellent, exceptionally comprehensive, and well-structured reference on a wide range of inferential tests and measures of association, which is ideal for the applied scientist. After a few useful introductory chapters that provide definitions and outline the main concepts involved in inferential statistics, the various tests are covered chapter by chapter. Each chapter contains sections describing:
1. the hypotheses evaluated and relevant background information;
2. examples of the kind of problems that can be addressed using the test
3. the null and alternative hypotheses;
4. computation (including meticulously worked out examples so the reader can follow the precise workings);
5. an extensive set of notes describing the interpretation of the results, the assumptions of the test, the robustness of the test to violations of those assumptions, and comparisons with alternative tests;
6. a set of references.
A set of decision tables are provided to assist the user in selecting the appropriate test, and there are additional extensive discussions in the various chapters to assist further if required. The book also includes an extensive list of look-up tables for significance testing. An additional valuable feature of the book is that in the chapter on the nonparametric test for a difference in medians of two populations (Mann-Whitney U-test) there is included discussions about permutation and randomization tests.

The target audience of the book is the practioner rather than the theoretician. The book aims to assist in the selection of an appropriate test and the interpretation of the test results rather than on a theoretical discussion of the test. The text is exceptionally clearly written, and is highly accessible to non-experts in statistics. There is a minimum of equations, which are supplied only where necessary. While it is not that hard to find a few editorial omissions, the book does seem to have been edited carefully, and I have as yet stumbled across only trivial errors. If I were forced to find any criticism, about the only thing I could say is that at the top of the page the chapter headings are listed purely in terms of test number without listing the test name, which sometimes makes it a little harder to find the test of interest.

I make absolutely no hesitation in recommending this book to anyone who makes use of inferential statistics.

The overall organization is very good. You will find the test you need with the help of the #guidline and decision table for selecting the appropriate statistical procedure# on page 113. The explanations given to the tests are very understandable. That means, you should be able to reproduce the examples given in the book with out problems. Additionally, at the end of each chapter is a bibliography for the test presented in this chapter. At the begining of each chapter some historical remark for the test are given.

This book is very good, because its contents is presented in a very good way. I can strongly recommend.

For any individual engaged in data analysis, this book is a godsend. In a single resource, you have a very comprehensive set of statistical tools. Also, they are presented in an extremely clear manner without getting bogged down in theory.

The layout is extremely helpful and greatly increases the value of the book. The table of contents and decision table are particularly well done. And, of course, the tables are all here as well!

Required!

Excellent book for handling all common and uncommon stats tests. Plenty of examples for application, an overview for each. This book is good for those that have had stats and need a reference guide on them later. I would not recommend this for anyone that has not actaully formally studied higher end stats.

Got it as a reference book to help me understand statistical tests. Havent used it much in my daily work, but its very comforting to know that its there. Quite readable, and extremely bulky to handle. Guess this will go on to be a classic in the field ..sad reality is that most of the methods discussed are already in programs like Minitab & S-Plus, so you can do most of the analysis without slogging through the theory.

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