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.... Since its first edition in 1997, Sheskin's encyclopedic compendium has been a helpful guide to the perplexed. ... The great value of the book is in its organization. ... This volume is an invaluable desk reference that, if consulted, should greatly increase the appropriateness of the experimental results on which much of CS relies. Its detailed discussions of both statistics in general and individual tests will hopefully encourage computer scientists to learn more of the underlying theory that makes these tests meaningful.
―Computing Reviews, July 2009
... 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, Universite de Nantes,
Journal of Applied Statistics, November 2007, Vol. 34, No. 9
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, University of Sheffield, 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, Vol. 49, No. 4
