Applied Non-Parametric Statistical Methods

This new edition of Peter Sprent's highly successful introduction to nonparametric methods retains many features acclaimed by reviewers of the first edition. Basics are simply and carefully explained using many realistic but simple examples. The text has been completely revised to highlight the way modern computer software enables us to carry out exact tests based on permutation distributions where one had previously to resort to asymptotic results in situations where these are now known to be misleading. New methods are introduced in this edition and relationships between inference procedures that may at first sight appear to be unrelated are clearly demonstrated. More attention is given to the analysis of censored data and the sections on analysis of counts and categorical data have been greatly extended. This additional material is relevant to applications in fields as diverse as medicine, the social sciences, industry and market research. This book should be of interest to research workers in industry, pharmaceutical firms, and all who use basic statistical methods. It should also be a useful text for undergraduate students taking university and polytechnic courses.

Strengths of this text certainly include its organization and writing style. Applied Nonparametric Statistical Methods provides a very clear exposition of modern nonparametric methods. Many students and practitioners will find it an excellent resource and reference for nonparametric statistics.
-Technometrics, 2003

... extremely valuable for statisticians as well as for researchers in applied fields. ... This well-written book is highly recommended for those readers who want to get a feeling for the nonparametric methods which they apply when analysing their data.
- Statistics in Medicine, 2004

About the Second Edition...
Nicely laid out for practitioners with minimal theory, very deliberate explanations, and lots of illustrations.
-Technometrics

This is the third edition of a very good book on nonparametric statistics...goes far beyond being a compendium of useful methods. It aims at promoting understanding as well. Good statistical practice is exemplified throughout... Particularly commendable are their discussions of multiple comparisons and conditioning in the two by two contingency table... If I could only have one book on nonparametric methods, this would be my choice. It is highly recommended.
-Short Book Reviews of the ISI, Vol. 21, No. 2, August, 2001