Nonparametric Statistics for The Behavioral Sciences

Rating:
Summary: an easy-to-follow tool book, but use w/ caution
Review: For a non math major (or stats major) user, this book offers an easy way to have works done quickly. But be cautious, an first-class cookbook does not necessarily yeild a first-class meal on your table.

Rating:
Summary: excellent and usable book on nonparametric statistics
Review: Speaking as an MPH level student, (i.e. not a real mathematician) this is about the only usable book on nonparametric stats I have encountered, so I ended up buying it despite the rather high price for a not terribly large book. But, as happens frequently in healthcare and social sciences, when faced with data that can't be analyzed with the normal mean and standard deviation stuff (i.e. survey answers, etc.) this book offers a lot of possibilities beyond the standard chi square test, and more importantly, is clear about what test is appropriate, and how to apply it.

Rating:
Summary: Excellent nonparametric statistics book
Review: This is (together with Empirical Methods for Artificial Intelligence by Paul R. Cohen) the best of the statistics books I read.

Rating:
Summary: Excellent first book for nonparametric stat methods
Review: This is an excellent first book for nonparametric statistical methods. It is a cookbook, but is a good introduction to the many nonparametric techniques for assessing data. These are oftentimes much better suited for your data than the standard stuff you get in intro to statistics. The book by David J. Sheskin or by Conover should your next book.

Rating:
Summary: Excellent first book for nonparametric stat methods
Review: This is an excellent first book for nonparametric statistical methods. It is a cookbook, but is a good introduction to the many nonparametric techniques for assessing data. These are oftentimes much better suited for your data than the standard stuff you get in intro to statistics. The book by David J. Sheskin or by Conover should your next book.