Cover image for Nonparametric Statistical Methods.
Nonparametric Statistical Methods.
Title:
Nonparametric Statistical Methods.
Author:
Hollander, Myles.
ISBN:
9781118677995
Personal Author:
Edition:
3rd ed.
Physical Description:
1 online resource (844 pages)
Series:
Wiley Series in Probability and Statistics ; v.751

Wiley Series in Probability and Statistics
Contents:
Cover -- Title Page -- Contents -- Preface -- Chapter 1 Introduction -- 1.1. Advantages of Nonparametric Methods -- 1.2. The Distribution-Free Property -- Distribution-Free Test Statistic -- 1.3. Some Real-World Applications -- 1.4. Format and Organization -- Procedure -- Large-Sample Approximation -- Ties -- Example -- Comments -- Properties -- Problems -- Efficiency -- 1.5. Computing with R -- 1.6. Historical Background -- Chapter 2 The Dichotomous Data Problem -- Introduction -- 2.1. A Binomial Test -- Procedure -- Large-Sample Approximation -- Comments -- Properties -- Problems -- 2.2. An Estimator for the Probability of Success -- Procedure -- Properties -- Problems -- 2.3. A Confidence Interval for the Probability of Success (Wilson) -- Procedure -- Properties -- Problems -- 2.4. Bayes Estimators for the Probability of Success -- Procedure -- Comments -- Properties -- Problems -- Chapter 3 The One-Sample Location Problem -- Introduction -- Paired Replicates Analyses by Way of Signed Ranks -- 3.1. A Distribution-Free Signed Rank Test (Wilcoxon) -- Hypothesis -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 3.2. An Estimator Associated with Wilcoxon's Signed Rank Statistic (Hodges-Lehmann) -- Procedure -- Comments -- Properties -- Problems -- 3.3. A Distribution-Free Confidence Interval Based on Wilcoxon's Signed Rank Test (Tukey) -- Procedure -- Large-Sample Approximation -- Comments -- Properties -- Problems -- Paired Replicates Analyses by Way of Signs -- 3.4. A Distribution-Free Sign Test (Fisher) -- Hypothesis -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 3.5. An Estimator Associated with the Sign Statistic (Hodges-Lehmann) -- Procedure -- Comments -- Properties -- Problems.

3.6. A Distribution-Free Confidence Interval Based on the Sign Test (Thompson, Savur) -- Procedure -- Large-Sample Approximation -- Comments -- Properties -- Problems -- One-Sample Data -- 3.7. Procedures Based on the Signed Rank Statistic -- Procedures -- Comments -- Properties -- Problems -- 3.8. Procedures Based on the Sign Statistic -- Procedures -- Comments -- Properties -- Problems -- 3.9. An Asymptotically Distribution-Free Test of Symmetry (Randles-Fligner-Policello-Wolfe, Davis-Quade) -- Hypothesis -- Procedure -- Ties -- Comments -- Properties -- Problems -- Bivariate Data -- 3.10. A Distribution-Free Test for Bivariate Symmetry (Hollander) -- Hypothesis -- Procedure -- Comments -- Properties -- Problems -- 3.11. Efficiencies of Paired Replicates and One-Sample Location Procedures -- Chapter 4 The Two-Sample Location Problem -- Introduction -- 4.1. A Distribution-Free Rank Sum Test (Wilcoxon, Mann and Whitney) -- Hypothesis -- Procedure -- Large-Sample Approximation -- Ties -- The Mann-Whitney Statistic -- Comments -- Properties -- Problems -- 4.2. An Estimator Associated with Wilcoxon's Rank Sum Statistic (Hodges-Lehmann) -- Procedure -- Comments -- Properties -- Problems -- 4.3. A Distribution-Free Confidence Interval Based on Wilcoxon's Rank Sum Test (Moses) -- Procedure -- Large-Sample Approximation -- Comments -- Properties -- Problems -- 4.4. A Robust Rank Test for the Behrens-Fisher Problem (Fligner-Policello) -- Hypothesis -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 4.5. Efficiencies of Two-Sample Location Procedures -- Chapter 5 The Two-Sample Dispersion Problem and Other Two-Sample Problems -- Introduction -- 5.1. A Distribution-Free Rank Test for Dispersion-Medians Equal (Ansari-Bradley) -- Hypothesis -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties.

Problems -- 5.2. An Asymptotically Distribution-Free Test for Dispersion Based on the Jackknife-Medians Not Necessarily Equal (Miller) -- Hypothesis -- Procedure -- Ties -- Comments -- Properties -- Problems -- 5.3. A Distribution-Free Rank Test for Either Location or Dispersion (Lepage) -- Hypothesis -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 5.4. A Distribution-Free Test for General Differences in Two Populations (Kolmogorov-Smirnov) -- Hypothesis -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 5.5. Efficiencies of Two-Sample Dispersion and Broad Alternatives Procedures -- Chapter 6 The One-Way Layout -- Introduction -- Hypothesis -- 6.1. A Distribution-Free Test for General Alternatives (Kruskal-Wallis) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 6.2. A Distribution-Free Test for Ordered Alternatives (Jonckheere-Terpstra) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 6.3. Distribution-Free Tests for Umbrella Alternatives (Mack-Wolfe) -- 6.3A. A Distribution-Free Test for Umbrella Alternatives, Peak Known (Mack-Wolfe) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 6.3B. A Distribution-Free Test for Umbrella Alternatives, Peak Unknown (Mack-Wolfe) -- Procedure -- Ties -- Comments -- Problems -- 6.4. A Distribution-Free Test for Treatments Versus a Control (Fligner-Wolfe) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- Rationale For Multiple Comparison Procedures.

6.5. Distribution-Free Two-Sided All-Treatments Multiple Comparisons Based on Pairwise Rankings-General Configuration (Dwass, Steel, and Critchlow-Fligner) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 6.6. Distribution-Free One-Sided All-Treatments Multiple Comparisons Based on Pairwise Rankings-Ordered Treatment Effects (Hayter-Stone) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 6.7. Distribution-Free One-Sided Treatments-Versus-Control Multiple Comparisons Based on Joint Rankings (Nemenyi, Damico-Wolfe) -- Procedure -- Large-Sample Approximations -- Ties -- Comments -- Properties -- Problems -- 6.8. Contrast Estimation Based on Hodges-Lehmann Two-Sample Estimators (Spjotvoll) -- Procedure -- Comments -- Properties -- Problems -- 6.9. Simultaneous Confidence Intervals for All Simple Contrasts (Critchlow-Fligner) -- Procedure -- Large-Sample Approximation -- Comments -- Properties -- Problems -- 6.10. Efficiencies of One-Way Layout Procedures -- Chapter 7 The Two-Way Layout -- Introduction -- Hypothesis -- 7.1. A Distribution-Free Test for General Alternatives in a Randomized Complete Block Design (Friedman, Kendall-Babington Smith) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 7.2. A Distribution-Free Test for Ordered Alternatives in a Randomized Complete Block Design (Page) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- Rationale for Multiple Comparison Procedures.

7.3. Distribution-Free Two-Sided All-Treatments Multiple Comparisons Based on Friedman Rank Sums-General Configuration (Wilcoxon, Nemenyi, McDonald-Thompson) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 7.4. Distribution-Free One-Sided Treatments Versus Control Multiple Comparisons Based on Friedman Rank Sums (Nemenyi, Wilcoxon-Wilcox, Miller) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 7.5. Contrast Estimation Based on One-Sample Median Estimators (Doksum) -- Procedure -- Comments -- Properties -- Problems -- Incomplete Block Data-Two-Way Layout with Zero or One Observation Per Treatment-Block Combination -- 7.6. A Distribution-Free Test for General Alternatives in a Randomized Balanced Incomplete Block Design (BIBD) (Durbin-Skillings-Mack) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- 7.7. Asymptotically Distribution-Free Two-Sided All-Treatments Multiple Comparisons for Balanced Incomplete Block Designs (Skillings-Mack) -- Procedure -- Ties -- Comments -- Properties -- Problems -- 7.8. A Distribution-Free Test for General Alternatives for Data From an Arbitrary Incomplete Block Design (Skillings-Mack) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems -- Replications-Two-Way Layout with at Least One Observation for Every Treatment-Block Combination -- 7.9. A Distribution-Free Test for General Alternatives in a Randomized Block Design with an Equal Number c(>1) of Replications Per Treatment-Block Combination (Mack-Skillings) -- Procedure -- Large-Sample Approximation -- Ties -- Comments -- Properties -- Problems.

7.10. Asymptotically Distribution-Free Two-Sided All-Treatments Multiple Comparisons for a Two-Way Layout with an Equal Number of Replications in Each Treatment-Block Combination (Mack-Skillings).
Abstract:
Praise for the Second Edition "This book should be an essential part of the personal library of every practicing statistician."-Technometrics   Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and

first-year graduate courses in applied nonparametric statistics.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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