Sheskin Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition

5. Auflage 2011
ISBN: 978-1-4398-5804-2
Verlag: CRC Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 1928 Seiten

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.

Zielgruppe

Statisticians, biostatisticians, psychologists, sociologists, engineers, and students.

Autoren/Hrsg.

Sheskin, David J.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

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

Über Autor(innen)

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