Sheskin D. Handbook of Parametric and Nonparametric Statistical Procedures

5th Edition. — CRC Press, 2020. — 1927 p. — ISBN: 9780429186196.Following in the footsteps of its bestselling predecessors, this Handbook, 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 varianceBroad 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.The Single-Sample Test
The Single Sample Test for Evaluating Population Skewness
The Wilcox on Signed Ranks Test
The Binomial Sign Test for a Single Sample
The MannWhitney U T est
The Kolmogorov-Smirnov Test for Two Independent Samples
The Test for Two Dependent Samples
The Wilcox on Matched-Pairs Signed-RanksT est
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 for k Independent Samples
The Single-Factor Within-Subjects Analysis of Variance
The Friedman Two Way Analysis of Variance by Ranks
The Cochran Q T est
The Between-Subjects Factorial Analysis of Variance
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
Multiple Regression
Hotelling’s T2
Multivariate Analysis of Covariance
Discriminant Function Analysis
Canonical Correlation
Logistic Regression
Principal Components Analysis and Factor Analysis
Path Analysis
Structural Equation Modeling
Meta Analysis
Appendix: Tables