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Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition, by David J. Sheskin
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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.
- Sales Rank: #910445 in Books
- Brand: Brand: Chapman and Hall/CRC
- Published on: 2011-04-27
- Original language: English
- Number of items: 1
- Dimensions: 10.10" h x 2.60" w x 7.30" l, 5.35 pounds
- Binding: Hardcover
- 1926 pages
- Used Book in Good Condition
Review
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
About the Author
David Sheskin is Professor of Psychology at Western Connecticut State University with a specialization in statistics and research design.
Most helpful customer reviews
18 of 19 people found the following review helpful.
Comprehensive and With Examples
By Random Customer
If you are looking for a comprehensive book that explains virtually every statistical procedures and testing, you simply have to have this book. It covers everything from simple t test to Kolmogorov-Smirnov test and others. Simply put, it's very readable and encyclopedic. Every chapter is illustrated with at least one example on how to compute the test.
The format of each chapter is as follows:
1. Background / Motivation to do the test
2. Sets of equations pertaining to the test
3. Sets of examples to illustrate the author's point
4. How to interpret the test
5. Any special cases of the test plus examples
6. References
Note that you won't find any proofs for the equations presented in the book. The appendix contains the table needed to perform the statistical analysis.
Here's partial list of tests covered in the third edition:
1. z test (Single-sample, two independent samples)
2. t test (Single-sample, two independent samples, two dependent samples)
3. Chi-Square Test for Population Variance (Single-sample)
4. Test for population skewness (Single-sample)
5. Test for Population kurtosis (Single-sample)
6. Wilcoxon Signed-Ranks test (Single, Matched-pairs)
7. Kolmogorov-Smirnov Goodness-of-Fit (Single-sample, two independent samples)
8. Lilliefors test for normality
9. Chi-Square Goodness-of-Fit test
10. Binomial Sign test (Single-sample, two dependent samples)
11. Runs Test (Single Sample)
12. Frequency test, maximum test, coupon collector's test, gap test, poker test, mean square successive difference test (for serial randomness).
13. Hartley's F-max test, Cohen's d index, Omega squared / eta squared tests
14. Mann-Whitney U Test
15. Siegel-Tukey test for equal variability
16. Moses Test for equal variability
17. Chi-Square test for r x c table
18. Contingency coefficient, Cramer's phi coeff, phi coeff, Cohen's kappa, Yule's Q, etc
19. Fisher exact test
20. McNemar test
21. Single-Factor between-subjects ANOVA
22. Kruskal-Wallis (one way) by ranks
23. Jonkheere-Terpstra test for ordered alternatives
24. Bowker test for internal symmetry
25. Stuart-Maxell test for marginal homogeneity
26. Van der Waerden Normal Scores test for k independent samples
27. Single-Factor Within-subjects ANOVA
28. Multiple t test, Fisher's LSD, Bonferroni-Dunn, Tukey's HSD, Newman-Keuls, Scheffe, Dunnet tests
29. Friedman Two-way ANOVA by Ranks.
30. Cochran's Q Test
31. Between-Subjects Factorial ANOVA
32. Pearson product-moment correlation coeff
33. Spearman's rank-order correlation
34. Kendall's Tau
35. Kendall's Coefficient of Concordance
36. Goodman and Kruskal's Gamma
Though it's nice to have the table in the appendix, I would prefer the book to contain the formula to compute the distribution itself. It would be very valuable for engineers who need to perform the test in computer programs, because not all distributions are available on the internet, like Tukey's HSD.
But this is minor enough. I wholeheartedly give this book a 5-star rating.
7 of 8 people found the following review helpful.
Extraordinary encyclopedia of statistics
By Harvey Motulsky
This is an amazing comprehensive (1736 pages) encyclopedia of statistics. It gives every variation on every test, with detailed examples and tables. It has plenty of equations for those who want to do calculations themselves. But it is does not derive any equations or prove any theorems. It explains concepts in words (with examples), not equations. This makes it quite understandable by scientists (as well as statisticians). It is extremely well written. Although it purports to be comprehensive, no book really can be. It makes no mention of nonlinear regression, or model comparisons. Its coverage of survival curves is a bit weak (compared to the rest of the book), as is its coverage of modern (computer intensive) statistical methods. If you analyze data, you should have access to this book as a reference. No other book is so comprehensive and yet readable. Its price, per page, makes it an amazing bargain.
1 of 1 people found the following review helpful.
Good reference
By JoeT
For all the basic statistical tests, this book makes for a great reference.
Many worked examples (by hand) so you can see how it's all done, followed by really excellent explanations on how to interpret the results.
However, a word of caution: as I stated above "basic statistical tests". Do not expect the same treatment for some of the more exotic tests like factor analysis or principal component analysis. It's just not there.
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