Nonparametric Statistical Methods 3rd Edition by Myles Hollander, Douglas Wolfe, Eric Chicken – Ebook PDF Instant Download/Delivery: 9781118677995 ,1118677994
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ISBN 10: 1118677994
ISBN 13: 9781118677995
Author: Myles Hollander, Douglas Wolfe, Eric Chicken
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.
Nonparametric Statistical Methods 3rd Edition Table of contents:
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-Qu
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 Nece
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-Gene
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
6.6. Distribution-Free One-Sided All-Treatments Multiple Comparisons Based on Pairwise Rankings-Orde
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
6.7. Distribution-Free One-Sided Treatments-Versus-Control Multiple Comparisons Based on Joint Ranki
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 (Friedm
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-Gen
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
7.4. Distribution-Free One-Sided Treatments Versus Control Multiple Comparisons Based on Friedman Ra
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 Des
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
7.7. Asymptotically Distribution-Free Two-Sided All-Treatments Multiple Comparisons for Balanced Inc
Procedure
Ties
Comments
Properties
Problems
7.8. A Distribution-Free Test for General Alternatives for Data From an Arbitrary Incomplete Block D
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 Nu
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
7.10. Asymptotically Distribution-Free Two-Sided All-Treatments Multiple Comparisons for a Two-Way L
Procedure
Ties
Comments
Properties
Problems
Analyses Associated with Signed Ranks
7.11. A Test Based on Wilcoxon Signed Ranks for General Alternatives in a Randomized Complete Block
Procedure
Ties
Comments
Properties
Problems
7.12. A Test Based on Wilcoxon Signed Ranks for Ordered Alternatives in a Randomized Complete Block
Procedure
Ties
Comments
Properties
Problems
7.13. Approximate Two-Sided All-Treatments Multiple Comparisons Based on Signed Ranks (Nemenyi)
Procedure
Ties
Comments
Properties
Problems
7.14. Approximate One-Sided Treatments-Versus-Control Multiple Comparisons Based on Signed Ranks (Ho
Procedure
Ties
Comments
Properties
Problems
7.15. Contrast Estimation Based on the One-Sample Hodges-Lehmann Estimators (Lehmann)
Procedure
Comments
Properties
Problems
7.16. Efficiencies of Two-Way Layout Procedures
Chapter 8 The Independence Problem
Introduction
8.1. A Distribution-Free Test for Independence Based on Signs (Kendall)
Hypothesis
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
8.2. An Estimator Associated with the Kendall Statistic (Kendall)
Procedure
Comments
Properties
Problems
8.3. An Asymptotically Distribution-Free Confidence Interval Based on the Kendall Statistic (Samara-
Procedure
Comments
Properties
Problems
8.4. An Asymptotically Distribution-Free Confidence Interval Based on Efron’s Bootstrap
Procedure
Comments
Properties
Problems
8.5. A Distribution-Free Test for Independence Based on Ranks (Spearman)
Hypothesis
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
8.6. A Distribution-Free Test for Independence Against Broad Alternatives (Hoeffding)
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
8.7. Efficiencies of Independence Procedures
Chapter 9 Regression Problems
Introduction
One Regression Line
9.1. A Distribution-Free Test for the Slope of the Regression Line (Theil)
Hypothesis
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
9.2. A Slope Estimator Associated with the Theil Statistic (Theil)
Procedure
Comments
Properties
Problems
9.3. A Distribution-Free Confidence Interval Associated with the Theil Test (Theil)
Procedure
Large-Sample Approximation
Comments
Properties
Problems
9.4. An Intercept Estimator Associated with the Theil Statistic and Use of the Estimated Linear Rela
Procedure
Comments
Problems
k(>2) Regression Lines
9.5. An Asymptotically Distribution-Free Test for the Parallelism of Several Regression Lines (Sen,
Hypothesis
Procedure
Ties
Comments
Properties
Problems
General Multiple Linear Regression
9.6. Asymptotically Distribution-Free Rank-Based Tests for General Multiple Linear Regression (Jaeck
Hypothesis
Procedure
Ties
Comments
Properties
Problems
Nonparametric Regression Analysis
9.7. An Introduction to Non-Rank-Based Approaches to Nonparametric Regression Analysis
9.8. Efficiencies of Regression Procedures
Chapter 10 Comparing Two Success Probabilities
Introduction
10.1. Approximate Tests and Confidence Intervals for the Difference between Two Success Probabilitie
Large-Sample Test Procedures
The 2 × 2 Chi-Squared Test of Homogeneity
The 2 × 2 Chi-Squared Test of Independence
Comments
Properties
Problems
10.2. An Exact Test for the Difference between Two Success Probabilities (Fisher)
Comments
Properties
Problems
10.3. Inference for the Odds Ratio (Fisher, Cornfield)
Unconditional Procedures
Confidence Intervals
Comments
Properties
Problems
10.4. Inference for $k$ Strata of 2×2 Tables (Mantel and Haenszel)
Approximate Conditional Procedure
Comments
Properties
Problems
10.5. Efficiencies
Chapter 11 Life Distributions and Survival Analysis
Introduction
11.1. A Test of Exponentiality Versus IFR Alternatives (Epstein)
Hypothesis
Procedure
Large-Sample Approximation
Comments
Properties
Problems
11.2. A Test of Exponentiality Versus NBU Alternatives (Hollander-Proschan)
Hypothesis
Procedure
Large-Sample Approximation
Ties
Comments
Properties
Problems
11.3. A Test of Exponentiality Versus DMRL Alternatives (Hollander-Proschan)
Hypothesis
Procedure
Large-Sample Approximation
Comments
Properties
Problems
11.4. A Test of Exponentiality Versus a Trend Change in Mean Residual Life (Guess-Hollander-Proschan
Hypothesis
Procedure
Comments
Properties
Problems
11.5. A Confidence Band for the Distribution Function (Kolmogorov)
Large-Sample Approximation
Comments
Properties
Problems
11.6. An Estimator of the Distribution Function When the Data are Censored (Kaplan-Meier)
Procedure
Comments
Properties
Problems
11.7. A Two-Sample Test for Censored Data (Mantel)
Procedure
Comments
Properties
Problems
11.8. Efficiencies
Chapter 12 Density Estimation
Introduction
12.1. Density Functions and Histograms
Properties of Densities
The Histogram
Procedure
Comments
Properties
Problems
12.2. Kernel Density Estimation
Centered Histogram
Kernels
Comments
Properties
Problems
12.3. Bandwidth Selection
Fixed Bandwidth
Variable Bandwidth
Comments
Problems
12.4. Other Methods
Chapter 13 Wavelets
Introduction
13.1. Wavelet Representation of a Function
Basis Functions
Multiresolution Analysis
Discrete Wavelet Transform
Comments
Properties
Problems
13.2. Wavelet Thresholding
Sparsity
Thresholding
Other Thresholding Methods
Comments
Properties
Problems
13.3. Other Uses of Wavelets in Statistics
Chapter 14 Smoothing
Introduction
14.1. Local Averaging (Friedman)
Comments
Problems
14.2. Local Regression (Cleveland)
Comments
Properties
Problems
14.3. Kernel Smoothing
Comments
Properties
Problems
14.4. Other Methods of Smoothing
Chapter 15 Ranked Set Sampling
Introduction
15.1. Rationale and Historical Development
15.2. Collecting a Ranked Set Sample
Comments
Problems
15.3. Ranked Set Sampling Estimation of a Population Mean
Procedure
Properties of μˆ RSS
Comparison of SRS and RSS Estimators
Comments
Properties
Problems
15.4. Ranked Set Sample Analogs of the Mann-Whitney-Wilcoxon Two-Sample Procedures (Bohn-Wolfe)
Hypothesis
Procedure
Large-Sample Approximation
Ties
Comments
Example.
Properties
Problems
15.5. Other Important Issues for Ranked Set Sampling
Set Size
Imperfect Rankings
Unbalanced Ranked Set Sampling
Unequal Set Sizes
Cost Considerations
Multiple Observations per Set
Problems
15.6. Extensions and Related Approaches
Judgment Post-Stratification
Order Restricted Randomization
Intentionally Representative Sampling
Sampling from Partially Rank-Ordered Sets
Chapter 16 An Introduction to Bayesian Nonparametric Statistics via the Dirichlet Process
Introduction
16.1. Ferguson’s Dirichlet Process
Comments
16.2. A Bayes Estimator of the Distribution Function (Ferguson)
Procedure
Comments
Properties
Problems
16.3. Rank Order Estimation (Campbell and Hollander)
Procedure
Comments
Properties
Problems
16.4. A Bayes Estimator of the Distribution When the Data are Right-Censored (Susarla and Van Ryzin)
Procedure
Comments
Properties
Problems
16.5. Other Bayesian Approaches
Other Priors
Gibbs Sampling
Gibbs Sampling with the Dirichlet
Repair Models and Partition-Based Priors
Bibliography
R Program Index
Author Index
Subject Index
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