Nonparametric statistical methods
This 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 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. 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.
24 pages matching asymptotic relative efficiency in this book
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The D1chotomous Data Problem
The OneSample Locat1on Problem
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accept H0 applied asymptotic efficiency asymptotic relative efficiency asymptotically distribution-free test Bernoulli trials calculate Chapter chorioamnion compute confidence coefficient continuous population continuous random variable corresponding data of Table denote differences distribution function distribution-free confidence interval Doksum empirical distribution function equal equation equivalent terminology Example experimentwise error rate graphical procedure H0 is true Hodges and Lehmann integer jackknife joint ranking large sample approximation level of significance median multiple comparison procedure mutually independent null distribution null hypothesis observations obtained one-sample one-sided test ooooo ordered values percentile point point estimator PROBLEMS procedures based procedures of Sections Properties random member random variable reject H0 respect Shorack sign statistic sign test signed rank statistic signed rank test specified standard deviation subgroup symmetric test based test of H0 test procedures tied group tion two-sample two-sided type I error underlying population usage variance versus the alternative Wilcoxon