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- DescriptionThe most accessible introduction to the theory and practice of multivariate analysis Multivariate Statistical Inference and Applications is a user-friendly introduction to basic multivariate analysis theory and practice for statistics majors as well as nmajors with little or background in theoretical statistics. Among the many special features of this extremely accessible first text on multivariate analysis are: Clear, step-by-step explanations of all key concepts and procedures along with original, easy-to-follow proofs Numerous problems, examples, and tables of distributions Many real-world data sets drawn from a wide range of disciplines Reviews of univariate procedures that give rise to multivariate techniques An extensive survey of the world literature on multivariate analysis An in-depth review of matrix theory A disk including all the data sets and SAS command files for all examples and numerical problems found in the book These same features also make Multivariate Statistical Inference and Applications an excellent professional resource for scientists and clinicians who need to acquaint themselves with multivariate techniques. It can be used as a stand-alone introduction or in concert with its more methods-oriented sibling volume, the critically acclaimed Methods of Multivariate Analysis.
- Author BiographyALVIN C. RENCHER, PhD, is Professor of Statistics at Brigham Young University and a Fellow of the American Statistical Association. He is the author of Methods of Multivariate Analysis and has written articles for Biometrics, Technometrics, Biometrika, Communications in Statistics, and American Statistician.
- Author(s)Alvin C. Rencher
- PublisherJohn Wiley and Sons Ltd
- Date of Publication09/01/1998
- Series TitleWiley Series in Probability and Statistics
- Place of PublicationNew York
- Country of PublicationUnited States
- ImprintJohn Wiley & Sons Inc
- Content NoteIllustrations
- Weight994 g
- Width169 mm
- Height244 mm
- Spine37 mm
- Contained items statementContains Diskette
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