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15-Jul-2008 Handbook of Parametric & Non-parametric Statistical procedures

Book coverA few readers have e-mailed to ask for more information about the book by David J. Sheskin we alluded to in the comment reply re: the Statistical test advisor, last week.

The book is the Handbook of Parametric & Non-parametric Statistical procedures, by David J. Sheskin, ISBN: 1584888148.

We have the third edition of the book which runs to over 1,200 pages -- a phenomenal piece of work for a single (obviously very dedicated) author. While it’s not a book you would sit down and read cover-to-cover, it is a very readable reference guide, covering all the parametric and non-parametric statistical procedures included in Analyse-it. 

For beginners the book starts at the very beginning, introducing summary statistics such as the mean, median, then moving on to explain concepts such as measurement scales, central tendency, variability, normal distribution, hypothesis testing, parametric and non-parametric statistics. The text is concise, but is clear, easy to read, and easy to understand -- ideal for anyone needing a refresher course on statistics.

Over 130 statistical tests for univariate and bivariate data are then covered, including ANOVA, Chi-Square, t- test, Mann-Whitney, Wilcoxon Signed Ranks, and many more. The historical background, purpose, use, assumptions and interpretation are explained, with examples to demonstrate real-world use of the test in business, education, life and environment science applications. Again, the text is very easy to read, and the extensive use of examples really helps to demonstrate how the tests are used in practical situations.

For experts the book includes formulas (without resorting to proofs) and explains how to calculate each test and statistic. References to further reading are included but aren’t needed as this book covers each procedure so thoroughly.

Of all the books we've read, this is hands-down, the definitive guide for univariate and bivariate statistical analysis. We haven't found another book so comprehensive and complete, yet easy to read and understand. The author really does succeed in his aim: to provide a comprehensive reference for readers at all levels.

The fourth edition of this book was published last year, with over 500 new pages, now covering topics such as multivariate analysis, clinical trials and survival analysis.

You can read more about the book and buy it online at Amazon (UK) and Amazon (US).

 

Contents (from the 3rd edition):
Introduction 1
Outline of Inferential Statistical Tests and Measures of Correlation/Association 107
Guidelines and Decision Tables for Selecting the Appropriate Statistical Procedure 113
Inferential Statistical Tests Employed with a Single Sample 119
The Single-Sample z Test 121
The Single-Sample t Test 135
The Single-Sample Chi-Square Test for a Population Variance 161
The Single-Sample Test for Evaluating Population Skewness 173
The Single-Sample Test for Evaluating Population Kurtosis 181
The Wilcoxon Signed-Ranks Test 189
The Kolmogorov-Smirnov Goodness-of-Fit Test for a Single Sample 203
The Chi-Square Goodness-of-Fit Test 219
The Binomial Sign Test for a Single Sample 245
The Single-Sample Runs Test (and Other Tests of Randomness) 337
Inferential Statistical Tests Employed with Two Independent Samples (and Related Measures of Association/Correlation) 373
The t Test for Two Independent Samples 375
The Mann-Whitney U Test 423
The Kolmogorov-Smirnov Test for Two Independent Samples 453
The Siegel-Tukey Test for Equal Variability 465
The Moses Test for Equal Variability 479
The Chi-Square Test for r x c Tables (Test 16a: The Chi-Square Test for Homogeneity; Test 16b: The Chi-Square Test of Independence (employed with a single sample)) 493
Inferential Statistical Tests Employed with Two Dependent Samples (and Related Measures of Association/Correlation) 573
The t Test for Two Dependent Samples 575
The Wilcoxon Matched-Pairs Signed-Ranks Test 609
The Binomial Sign Test for Two Dependent Samples 621
The McNemar Test 633
Inferential Statistical Tests Employed with Two or More Independent Samples (and Related Measures of Association/Correlation) 665
The Single-Factor Between-Subjects Analysis of Variance 667
The Kruskal-Wallis One-Way Analysis of Variance by Ranks 757
The Van der Waerden Normal-Scores Test for k Independent Samples 781
Inferential Statistical Tests Employed with Two or More Dependent Samples (and Related Measures of Association/Correlation) 795
The Single-Factor Within-Subjects Analysis of Variance 797
The Friedman Two-Way Analysis of Variance by Ranks 845
The Cochran Q Test 867
Inferential Statistical Test Employed with Factorial Design (and Related Measures of Association/Correlation) 885
The Between-Subjects Factorial Analysis of Variance 887
Measures of Association/Correlation 943
The Pearson Product-Moment Correlation Coefficient 945
Spearman's Rank-Order Correlation Coefficient 1061
Kendall's Tau 1079
Kendall's Coefficient of Concordance 1093
Goodman and Kruskal's Gamma 1109
Appendix: Tables 1123
Index 1175