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This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, 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 new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.

**Contents: **Preface. Introduction. Matrix Algebra. Multiple Regression. Two-Group Multivariate Analysis of Variance. *K Group MANOVA: A Priori and Post Hoc Procedures. Assumptions in MANOVA. Discriminant Analysis. Factorial Analysis of Variance. Analysis of Covariance. Stepdown Analysis. Confirmatory and Exploratory Factor Analysis. Canonical Correlation. Repeated Measures Analysis. Categorical Data Analysis: The Log Linear Model. Appendices: Statistical Tables. Data Sets. Obtaining Nonorthogonal Contrasts in Repeated Measures Designs.*

This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, 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 new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.

**Contents: **Preface. Introduction. Matrix Algebra. Multiple Regression. Two-Group Multivariate Analysis of Variance. *K Group MANOVA: A Priori and Post Hoc Procedures. Assumptions in MANOVA. Discriminant Analysis. Factorial Analysis of Variance. Analysis of Covariance. Stepdown Analysis. Confirmatory and Exploratory Factor Analysis. Canonical Correlation. Repeated Measures Analysis. Categorical Data Analysis: The Log Linear Model. Appendices: Statistical Tables. Data Sets. Obtaining Nonorthogonal Contrasts in Repeated Measures Designs.*

This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, 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 new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.

**Contents: **Preface. Introduction. Matrix Algebra. Multiple Regression. Two-Group Multivariate Analysis of Variance. *K Group MANOVA: A Priori and Post Hoc Procedures. Assumptions in MANOVA. Discriminant Analysis. Factorial Analysis of Variance. Analysis of Covariance. Stepdown Analysis. Confirmatory and Exploratory Factor Analysis. Canonical Correlation. Repeated Measures Analysis. Categorical Data Analysis: The Log Linear Model. Appendices: Statistical Tables. Data Sets. Obtaining Nonorthogonal Contrasts in Repeated Measures Designs.*

**Contents: **Preface. Introduction. Matrix Algebra. Multiple Regression. Two-Group Multivariate Analysis of Variance. **Appendices: **Statistical Tables. Data Sets. Obtaining Nonorthogonal Contrasts in Repeated Measures Designs.

**Contents: **Preface. Introduction. Matrix Algebra. Multiple Regression. Two-Group Multivariate Analysis of Variance. **Appendices: **Statistical Tables. Data Sets. Obtaining Nonorthogonal Contrasts in Repeated Measures Designs.

**Contents: **Preface. Introduction. Matrix Algebra. Multiple Regression. Two-Group Multivariate Analysis of Variance. **Appendices: **Statistical Tables. Data Sets. Obtaining Nonorthogonal Contrasts in Repeated Measures Designs.