Using multivariate statistics / Barbara G. Tabachnick, Linda S. Fidell

Includes bibliographical references and index

-- 1. Introduction -- 2. A guide to statistical techniques : Using the book -- 3. Review of univariate and bivariate statistics -- 4. Cleaning up your act: screening data prior to analysis -- 5. Multiple regression -- 6. Canonical correlation -- 7. Multiway frequency analysis -- 8. Analysis of Covariance -- 9. Multivariate analysis of variance and covariance -- 10. Profile analysis : the multivariate approach to repeated measures -- 11. Discriminant function analysis -- 12. Logistic regression -- 13. Principal components and factor analysis -- 14. Structural equation modeling / Jodie B. Ullman -- 15. Survival/failure analysis -- 16. Time-series analysis -- 17. An overview of the general linear model-- Appendix A : A skimpy introduction to matrix algebra -- Appendix B : Research designs for complete Examples -- Appendix C : Statistical tables

"This text takes a practical approach to multivariate data analysis, with an introduction to the most commonly encountered statistical and multivariate techniques. Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses through the most recent releases of SAS and SPSS. The book maintains its practical approach, still focusing on the benefits and limitations of applications of a technique to a data set - when, why, and how to do it. Overall, it provides advanced students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics."--Publisher's Web site