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 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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Studyguide for Nonparametric Statistical Methods by Hollander & Wolfe, ISBN ...
No preview available - 2006
The Dichotomous Data Problem
The OneSample Location Problem
The TwoSample Location Problem
12 other sections not shown
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apply approximate P-value associated Asymptotic Normality asymptotic relative efficiency asymptotically distribution-free average ranks Bernoulli trials bivariate block design bootstrap calculation censored chi-square chi-square distribution chorioamnion compute confidence bound confidence coefficient confidence interval continued corresponding critical values data in Table defined denote differences discussed distribution F distribution function distribution-free test equal equation exact Example experimentwise error rate exponential given in Table independent joint ranking Kaplan-Meier estimator large-sample approximation Lehmann liver scan Mann-Whitney mean residual median method Mini tab multiple comparison procedure nonparametric normal theory null hypothesis null variance obtained odds ratio one-sided ordered alternatives P-value parameter patients point estimator Problem Proschan random variables rank test regression Reject H0 replications sample sizes Section setting signed rank significance level StatXact tends to infinity test based test H0 test of H0 test procedure test statistic tied group treatment effects two-sample two-sided type I error underlying distribution upper-tail probabilities zero