Sheskin D.J. Handbook of Parametric and Nonparametric Statistical Procedures

Second Edition. — Chapman & Hall/CRC, 2000. — 1002 p. — ISBN: 1-58488-133-X.Called the "bible of applied statistics," the first edition of the bestselling Handbook of Parametric and Nonparametric Statistical Procedures was unsurpassed in its scope. The Second Edition goes even further - more tests, more examples, more than 250 pages of new material. If you have to
Decide what method of analysis to use,
Use a particular test for the first time,
Distinguish acceptable from unacceptable research,
Interpret the results of published studies,
the Handbook of Parametric and Nonparametric Statistical Procedures has the background, the answers, and the guidelines to get the job done. The book 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 book is also accessible to those lacking the theoretical or mathematical background required for understanding subject matter typically documented in statistics reference books.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 Chi-Square Test for a Population Variance.
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 [Test 16a: The Chi-Square Test for Homogeneity;
Test 16b: The Chi-Square Test of Independence (employed with a single sample)].
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 for k Independent samples.
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 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.
Appendix: Tables A1-A23.