Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition
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Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition

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Description

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.
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Product details

  • Hardback | 1926 pages
  • 190.5 x 254 x 66.04mm | 2,381.35g
  • Whittles Publishing
  • London, United Kingdom
  • English
  • New edition
  • 5th New edition
  • 1000+; 394 Tables, black and white; 128 Illustrations, black and white
  • 1439858012
  • 9781439858011
  • 56,530

Table of contents

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 x 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
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Review quote

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
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About David J. Sheskin

David Sheskin is Professor of Psychology at Western Connecticut State University with a specialization in statistics and research design.
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11 ratings
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1 9% (1)
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