Handbook of Parametric and Nonparametric Statistical Procedures, Fourth Edition | 
 enlarge | Author: David J. Sheskin
Publisher: Chapman & Hall/CRC
Category: Book
List Price: $139.95
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Rating:  2 reviews
Sales Rank: 163352
Media: Hardcover
Edition: 4
Pages: 1776
Number Of Items: 1
Shipping Weight (lbs): 4.8
Dimensions (in): 10.1 x 7.1 x 2.5
ISBN: 1584888148
Dewey Decimal Number: 519.5
EAN: 9781584888147
Publication Date: January 19, 2007
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Product Description
With more than 500 pages of new material, the Handbook of Parametric and Nonparametric Statistical Procedures, Fourth Edition carries on the esteemed tradition of the previous editions, providing up-to-date, in-depth coverage of now more than 160 statistical procedures. The book also discusses both theoretical and practical statistical topics, such as experimental design, experimental control, and statistical analysis. New to the Fourth Edition Multivariate statistics including matrix algebra, multiple regression, Hotellings T2, MANOVA, MANCOVA, discriminant function analysis, canonical correlation, logistic regression, and principal components/factor analysis Clinical trials, survival analysis, tests of equivalence, analysis of censored data, and analytical procedures for crossover design Regression diagnostics that include the Durbin-Watson test Log-linear analysis of contingency tables, Mantel-Haenszel analysis of multiple 2 2 contingency tables, trend analysis, and analysis of variance for a Latin square design Levene and Brown-Forsythe tests for evaluating homogeneity of variance, the Jarque-Bera test of normality, and the extreme studentized deviate test for identifying outliers Confidence intervals for computing the population median and the difference between two population medians The relationship between exponential and Poisson distribution Eliminating the need to search across numerous books, this handbook provides you with everything you need to know about parametric and nonparametric statistical procedures. It helps you choose the best test for your data, interpret the results, and better evaluate the research of others.
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| Customer Reviews:
Comprehensive and With Examples April 23, 2007
A Reader
10 out of 10 found this review helpful
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.
Reference for Researchers July 8, 2008
D´Ottaviano (Europe)
I really wonder what it takes to write a book like this. I do not have the earlier editions but this one is just as good as a tech book can ever be.
As a professional researcher, you might (quite often) face yourself in a situation where you thought you got the data you needed to make your point and at the end you find out there is this other (unpredicted) test your data should pass before your point is viewed as valid beyond doubt. And this book comes to rescue you in such situations.
The level of understanding of the subject matter required to digest the content is mostly intermediate, but it seems that the author has intentionally allocated adequate space for those looking for deeper insights as well.
Well worth the price.
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