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Multivariate analysis for the biobehavioral and social sciences : a graphical approach / Bruce L. Brown [and others].

Contributor(s): Brown, Bruce (Bruce L.).
Material type: materialTypeLabelBookPublisher: Hoboken, N.J. : Wiley, 2012Description: 1 online resource (xiv, 475 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9781118131626; 1118131622; 9781283332255; 1283332256; 9781118131596; 1118131592; 9781118131619; 1118131614.Subject(s): Social sciences -- Statistical methods | Multivariate analysis | Multivariate Analysis | Statistics as Topic | Social Sciences | Behavioral Research | MATHEMATICS -- Probability & Statistics -- Multivariate Analysis | Multivariate analysis | Social sciences -- Statistical methodsGenre/Form: Electronic books.Additional physical formats: Print version:: Multivariate Analysis for the Biobehavioral and Social Sciences.DDC classification: 300.1/519535 Online resources: Wiley Online Library
Contents:
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.
Summary: 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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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.

Includes bibliographical references and indexes.

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