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.
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THE ONESAMPLE LOCATION PROBLEM
Paired Replicates Analyses by Way of Signs
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accept H alternatives applied associated assume Assumptions asymptotically distribution-free average calculate Chapter coefficient Comment Comments compute confidence interval configurations consistent constant continuous corresponding data of Table decision defined denote depend described designed differences discussed distribution distribution-free test effect efficiency entry equal equation EQUIVALENT error estimator Example function given gives glucose Hollander hypothesis illustrate independent integer large sample approximation Lehmann mean median methods Moses multiple comparison procedure nonparametric Note null distribution observations obtained one-sided ordered pairs parameter particular perform point estimator population positive possible probability PROBLEMS procedure Properties random variable rank sum REFERENCES reject H replaced respect satisfies Section signed rank significance specified statistic subjects symmetric tends test of H test procedures tion treatment true two-sample two-sided upper USAGE values variance versus Wilcoxon