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Nonparametric Statistical Methods Hardcover – January 25, 1999

ISBN-13: 978-0471190455 ISBN-10: 0471190454 Edition: 2nd

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Product Details

  • Hardcover: 816 pages
  • Publisher: Wiley-Interscience; 2 edition (January 25, 1999)
  • Language: English
  • ISBN-10: 0471190454
  • ISBN-13: 978-0471190455
  • Product Dimensions: 7.3 x 1.7 x 10.3 inches
  • Shipping Weight: 3.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #996,822 in Books (See Top 100 in Books)

Editorial Reviews

Review

The second edition of Nonparametric Statistical Methods provides a complete, thorough, and in-depth presentation of various techniques in nonparametric statistics.-Journal of Quality Technology Vol. 33, No. 2, April 2001

"Hollander and Wolfe may have waited 25 years to update their book, but it would hardly have been possible for them to have done a new edition that is any more impressive than this second edition. ... This book should be an essential part of the personal library of every practicing statistician." (Technometrics, Vol. 41, No. 4, Nov. 1999)

From the Back Cover

The new edition of Hollander and Wolfe's classic text on nonparametric statistical methods.

The importance of nonparametric methods in modern statistics has grown dramatically since their inception in the mid-1930s. Requiring few or no assumptions about the populations from which data are obtained, they have emerged as the preferred methodology among statisticians and researchers performing data analysis. Today, these highly efficient techniques are being applied to an ever-widening variety of experimental designs in the social, behavioral, biological, and physical sciences.

This long-awaited Second Edition of Myles Hollander and Douglas A. Wolfe's successful Nonparametric Statistical Methods meets the needs of a new generation of users, with completely up-to-date coverage of this important statistical area. Like its highly acclaimed predecessor, the revised edition, along with its companion ftp site, aims to equip readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for a given situation. An extensive array of examples drawn from actual experiments illustrates clearly how to use nonparametric approaches to handle one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. Rewritten and updated, this Second Edition now includes new or expanded coverage of:
* Nonparametric regression methods
* The bootstrap
* Contingency tables and the odds ratio
* Life distributions and survival analysis
* Nonparametric methods for experimental designs.

Plus:
* More procedures, real-world data sets, and problems
* Illustrated examples using Minitab and StatXact

An ideal text for an upper-level undergraduate or first-year graduate course, Nonparametric Statistical Methods, Second Edition is also an invaluable source for professionals who want to keep abreast of the latest developments within this dynamic branch of modern statistics.

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Most Helpful Customer Reviews

26 of 26 people found the following review helpful By Michael R. Chernick on February 12, 2008
Format: Hardcover
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.
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25 of 27 people found the following review helpful By A Customer on June 24, 1999
Format: Hardcover
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.
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2 of 2 people found the following review helpful By A Sanders on October 1, 2007
Format: Hardcover Verified Purchase
It will take about 3 weeks to get used to the convoluted organization of this book. The explanations are actually fairly good, as are the examples, but the set up of text, comments, examples and problems is often difficult to follow. Tables are not where they are expected, references are circular, and so on. I will say that at least the system, as it is, is 'applied' consistently, so once you get used to it, it only slows understanding slightly. Of course, the editors were statiticians, not editors...
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1 of 1 people found the following review helpful By Justin Z. Smith on October 4, 2010
Format: Hardcover Verified Purchase
I fully recommend this book as part of one's nonparametric statistics library. It has wonderful detailing of the assumptions for the methods, and the book is tied together by a strong practical applications focus.
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By Ben Goldstein on September 10, 2009
Format: Hardcover
This book is great for what it is - an encyclopedia for non-parametric methods. This isn't the text to read for an exposition about the development and all theory and proof behind the method (Lehmann is great for that) this is the place to go where you say my data has such and such a structure, and I have such and such hypothesis about it. This doesn't mean that this is a cookie cutter book - it provides the assumptions about each tests, the formulas for hand calculation (great for checking if the R function was coded correctly!), the relative efficiencies, info about ties and the asymptotics. as well as the notes at the end. In this sense it has something for must levels. I agree though the tables are a bit silly and the price is a bit high

A couple of notes:
1) Some people have critiqued the structure - I actually like it but can see how it can be a bit confusing
2) The book is definitely about classic non-parametrics based on rank tests. There is much more to non-parametrics but this book fits a good niche

If you are a practitioner who realizes ANOVAs are silly you will get something out of this book. And if you have a good understanding of theory it won't feel too dumbed down.
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Format: Hardcover Verified Purchase
I highly recommend this book. Has very useful statistical tables in it as well as applied statistical concepts. Do not let the equations inside the book frighten you, but use them to guide you.
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