5th Edition

Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition

By David J. Sheskin Copyright 2011
    1926 Pages 128 B/W Illustrations
    by Chapman & Hall

    Following in the footsteps of its bestselling predecessors, the Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition provides researchers, teachers, and students with an all-inclusive reference on univariate, bivariate, and multivariate statistical procedures.

    New in the Fifth Edition:

    • Substantial updates and new material throughout
    • New chapters on path analysis, meta-analysis, and structural equation modeling
    • Index numbers and time series analysis applications in business and economics
    • Statistical quality control applications in industry
    • Random- and fixed-effects models for the analysis of variance

    Broad in scope, the Handbook is intended for individuals involved in a wide spectrum of academic disciplines encompassing the fields of mathematics, the social, biological, and environmental sciences, business, and education. A reference for statistically sophisticated individuals, the Handbook is also accessible to those lacking the theoretical or mathematical background required for understanding subject matter typically documented in statistics reference books.

    Introduction
    Outline of Inferential Statistical Tests and Measures of Correlation/Association
    Guidelines and Decision Tables for Selecting the Appropriate Statistical Procedure

    Inferential Statistical Tests Employed with a Single Sample
    The Single-Sample z Test
    The Single-Sample t Test
    The Single-Sample Test for Evaluating Population Skewness
    The Single-Sample Test for Evaluating Population Kurtosis
    The Wilcoxon Signed-Ranks Test
    The Kolmogorov–Smirnov Goodness-of-Fit Test for a Single Sample
    The Chi-Square Goodness-of-Fit Test
    The Binomial Sign Test for a Single Sample
    The Single-Sample Runs Test (and Other Tests of Randomness)

    Inferential Statistical Tests Employed with Two Independent Samples (and Related Measures of Association/Correlation)
    The t Test for Two Independent Samples
    The Mann–Whitney U Test
    The Kolmogorov–Smirnov Test for Two Independent Samples
    The Siegel–Tukey Test for Equal Variability
    The Moses Test for Equal Variability
    The Chi-Square Test for r × c Tables

    Inferential Statistical Tests Employed with Two Dependent Samples (and Related Measures of Association/Correlation)
    The t Test for Two Dependent Samples
    The Wilcoxon Matched-Pairs Signed-Ranks Test
    The Binomial Sign Test for Two Dependent Samples
    The McNemar Test

    Inferential Statistical Tests Employed with Two or More Independent Samples (and Related Measures of Association/Correlation)
    The Single-Factor Between-Subjects Analysis of Variance
    The Kruskal–Wallis One-Way Analysis of Variance by Ranks
    The van der Waerden Normal Scores Test

    Inferential Statistical Tests Employed with Two or More Dependent Samples (and Related Measures of Association/Correlation)
    The Single-Factor Within-Subjects Analysis of Variance
    The Friedman Two-Way Analysis of Variance by Ranks
    The Cochran Q Test

    Inferential Statistical Test Employed with a Factorial Design (and Related Measures of Association/Correlation)
    The Between-Subjects Factorial Analysis of Variance

    Measures of Association/Correlation
    The Pearson Product-Moment Correlation Coefficient
    Spearman’s Rank-Order Correlation Coefficient
    Kendall's Tau
    Kendall's Coefficient of Concordance
    Goodman and Kruskal's Gamma

    Multivariate Statistical Analysis
    Matrix Algebra and Multivariate Analysis
    Multiple Regression
    Hotelling’s T2
    Multivariate Analysis of Variance
    Multivariate Analysis of Covariance
    Discriminant Function Analysis
    Canonical Correlational
    Logistic Regression
    Principal Components Analysis and Factor Analysis
    Path Analysis
    Structural Equation Modeling
    Meta-Analysis

    Appendix: Tables
    Table of the Normal Distribution
    Table of Student’s t Distribution
    Power Curves for Student’s t Distribution
    Table of the Chi-Square Distribution
    Table of Critical T Values for Wilcoxon’s Signed-Ranks and Matched-Pairs Signed-Ranks Tests
    Table of the Binomial Distribution, Individual Probabilities
    Table of the Binomial Distribution, Cumulative Probabilities
    Table of Critical Values for the Single-Sample Runs Test
    Table of the Fmax Distribution
    Table of the F Distribution
    Table of Critical Values for Mann–Whitney U Statistic
    Table of Sandler’s A Statistic
    Table of the Studentized Range Statistic
    Table of Dunnett’s Modified t Statistic for a Control Group Comparison
    Graphs of the Power Function for the Analysis of Variance
    Table of Critical Values for Pearson r
    Table of Fisher’s zr Transformation
    Table of Critical Values for Spearman’s Rho
    Table of Critical Values for Kendall’s Tau
    Table of Critical Values for Kendall’s Coefficient of Concordance
    Table of Critical Values for the Kolmogorov–Smirnov Goodness-of-Fit Test for a Single Sample
    Table of Critical Values for the Lilliefors Test for Normality
    Table of Critical Values for the Kolmogorov–Smirnov Test for Two Independent Samples
    Table of Critical Values for the Jonckheere–Terpstra Test Statistic
    Table of Critical Values for the Page Test Statistic
    Table of Extreme Studentized Deviate Outlier Statistic
    Table of Durbin–Watson Test Statistic
    Constants Used for Estimation and Construction of Control
    Charts
    Index

    Biography

    David Sheskin is Professor of Psychology at Western Connecticut State University with a specialization in statistics and research design.

    all procedures are presented in detail. … it is a reference book par excellence. It is very well edited and produced. I cannot think of a single-volume text which is close to the range and depth of this handbook. Professor Sheskin writes clearly and accessibly … There is substantial material that any applied statistician, regardless of their interests or training, should know about and this handbook provides that and more in one remarkable volume. I am sure that this new edition of Sheskin’s handbook will be an extremely useful resource for researchers … and also an invaluable reference for teachers and students who are engaged in applied statistics courses. … I very much recommend it.
    —Mario Cortina-Borja, Journal of the Royal Statistical Society, Series A, 2012

    Praise for the Fourth Edition:
    I recommend this book for those who already know which statistical test they want to apply and who want to learn how to do it, step by step, from the data to the conclusion. I also recommend it for teachers who will find a lot of good examples they can use within their courses.
    —Philippe Castagliola, Journal of Applied Statistics, November 2007

    This book occupies a unique place in the literature. I am sure I will come back to it to check a statistical test.
    —Kostas Triantafyllopoulos, Significance, December 2007

    … provides both depth and breadth of coverage … I can safely recommend this book as a handy resource manual for researchers and applied practitioners as well as a textbook for students majoring in disciplines other than statistics.
    Technometrics, November 2007