Nonparametric Statistical MethodsThis 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. |
Contents
CHAPTER | 1 |
THE DICHOTOMOUS DATA PROBLEM | 20 |
THE ONESample LOCATION PROBLEM | 26 |
Copyright | |
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accept alternatives applied associated Assumptions asymptotic asymptotic efficiency asymptotically distribution-free average block calculate Chapter coefficient Comment Comments Compare compute confidence interval configurations consistent constant continuous corresponding data of Table decision defined denote depend designed determination deviation differences discussed distribution distribution-free distribution-free test efficiency entry equal equation equivalent estimator Example given gives glucose Hollander hypothesis illustrate independent large sample approximation Lehmann mean median method Moses n₁ n₂ nonparametric Note null distribution observations obtained one-sided ordered pairs parameter particular perform population positive possible probability PROBLEMS procedure Properties proposed R₁ R₂ random variable rank rank sum REFERENCES reject respect satisfies Section signed rank significance standard statistic subgroup subjects tends test based test procedures tion treatment true two-sample two-sided underlying upper USAGE values variance versus Wilcoxon X₁ Y₁