© 2009 – Routledge
This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half.
The new edition features:
Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.
"Of all the texts I have ever used, this is one of the very best… Students find the book to be extremely understandable … [and] nearly all keep [it] for reference purposes…It really is a great applied treatment of the topics… the examples are general enough to appeal to students across disciplines … The … computer examples are very helpful…an extraordinarily balanced text by a highly respected author." – Dale R. Fuqua, Oklahoma State University, USA
"It is the best text I have found on Multivariate stats… Including examples in journals is a great addition… the book's … greatest strengths [include] comprehensive coverage of the analyses, thorough description and discussion of the assumptions for the analyses, and annotated SPSS print-outs." – Philip Schatz, Saint Joseph's University, USA
"The book's primary strength is its exceptionally clear, even engaging, prose." – Louis M. Kyriakoudes, University of Southern Mississippi, USA
1. Introduction 2. Matrix Algebra 3. Multiple Regression 4. Two-Group Multivariate Analysis of Variance 5. K-Group MANOVA: A Priori and Post Hoc Procedures 6. Assumptions in MANOVA 7. Discriminant Analysis 8. Factorial Analysis of Variance 9. Analysis of Covariance 10. Stepdown Analysis 11. Exploratory and Confirmatory Factor Analysis 12. Canonical Correlation 13. Repeated Measures Analysis 14. Categorical Data Analysis: The Log Linear Model 15. Hierarchical Linear Modeling 16. Structural Equation Modeling. Appendix A: Statistical Tables. Appendix B: Obtaining Nonorthogonal Contrasts in Repeated Measures Designs. Answer Section.
The document Answers to Even Numbered Questions, is available to Instructors to access from the Instructor Downloads Page.