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Nonparametric Statistical Methods, 2nd Edition [Hardcover]

Myles Hollander (Author), Douglas A. Wolfe (Author)
4.1 out of 5 stars  See all reviews (8 customer reviews)

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Book Description

January 11, 1999 0471190454 978-0471190455 2
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 students 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.
* 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, this text is also an invaluable source for professionals who want to keep abreast of the latest developments within this dynamic branch of modern statistics.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.

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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.

Product Details

  • Hardcover: 787 pages
  • Publisher: Wiley-Interscience; 2 edition (January 11, 1999)
  • Language: English
  • ISBN-10: 0471190454
  • ISBN-13: 978-0471190455
  • Product Dimensions: 10.2 x 7.4 x 1.6 inches
  • Shipping Weight: 3.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (8 customer reviews)
  • Amazon Best Sellers Rank: #481,734 in Books (See Top 100 in Books)

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25 of 25 people found the following review helpful:
4.0 out of 5 stars revision of a classic on nonparametrics, February 12, 2008
This review is from: Nonparametric Statistical Methods, 2nd Edition (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:
5.0 out of 5 stars An excellent, encyclopediac approach, June 24, 1999
By A Customer
This review is from: Nonparametric Statistical Methods, 2nd Edition (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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1 of 1 people found the following review helpful:
3.0 out of 5 stars Material well covered, but organization is confusing, October 1, 2007
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This review is from: Nonparametric Statistical Methods, 2nd Edition (Hardcover)
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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Inside This Book (learn more)
First Sentence:
Roughly speaking, a nonparametric procedure is a statistical procedure that has certain desirable properties that hold under relatively mild assumptions regarding the underlying populations from which the data are obtained. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
using average ranks, human chorioamnion, tapeworm data, exact conditional null distribution, ath percentile point, bleeding time data, mini tab output, noncontrol treatments, null distribution tables, null expected value, distributions and survival analysis, plasma glucose data, apply the approximate procedure, combined samples ranks, conditional permutation distribution, exact power values, individual treatment sums, lesser snow geese leave, overnight roost sites, same continuous population, normal theory approximation, corresponding nominal level, additional critical values, tuna data, common underlying distribution
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, John Wiley, Mathematical Statistics, Monte Carlo, Journal of the American Statistical Association, Marcel Dekker, Historical Development, Pacific Grove, Profile Scales, Selected Tables, Acid Red, Asymptotic Multivariate Normality, Florida State University, Lake Michigan, Ohio State University, Procedure Let, Berkeley Symp, Hypothesis Let, Continuation of Example, Master Sgt, Other Noninvolved Treatments, Department of Statistics, Karate Kid, Kokosing Lake, Middle Ground
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