Includes bibliographical references and indexes.

Frontmatter -- Overview of Multivariate and Regression Methods -- The Seven Habits of Highly Effective Quants: A Review of Elementary Statistics Using Matrix Algebra -- Fundamentals of Matrix Algebra -- Factor Analysis and Related Methods: Quintessentially Multivariate -- Multivariate Graphics -- Canonical Correlation: The Underused Method -- Hotelling's as the Simplest Case of Multivariate Inference -- Multivariate Analysis of Variance -- Multiple Regression and the General Linear Model -- Appendices: Statistical Tables -- Name Index -- Subject Index.

Multivariate Analysis for the Social Sciences provides clear guidelines combined with the insight needed to understand the methods and applications of multivariate statistics. This easy-to-follow book provides students in social, behavioral, and health science-whose focus is not primarily in mathematics-with an abundance of chapter-ending questions and answers, including: conceptual questions about the meaning of each method; questions that test the reader's ability to carry out the computational procedures on simple datasets; and data analysis questions for using analytical packages to analyze both simplest case data and also to practice with more realistic datasets.

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