Synopses & Reviews
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.
Synopsis
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.
About the Author
MYLES HOLLANDER is Robert O. Lawton Distinguished Professor of Statistics at Florida State University in Tallahassee. He served as editor of the Theory and Methods Section of the Journal of the American Statistical Association from 1993-96.
DOUGLAS A. WOLFE is a Professor of Statistics at Ohio State University in Columbus. He is a two-time recipient of the Ohio State University Alumni Distinguished Teaching Award, in 1973-74 and 1988-89.
Table of Contents
The Dichotomous Data Problem.
The One-Sample Location Problem.
The Two-Sample Location Problem.
The Two-Sample Dispersion Problem and Other Two-Sample Problems.
The One-Way Layout.
The Two-Way Layout.
The Independence Problem.
Regression Problems.
Comparing Two Success Probabilities.
Life Distributions and Survival Analysis.
Appendix.
Bibliography.
Answers to Selected Problems.
Indexes.