Multivariate Statistical Inference and ApplicationsISBN: 9780471571513
592 pages
December 1997

The most accessible introduction to the theory and practice of multivariate analysis
Multivariate Statistical Inference and Applications is a userfriendly introduction to basic multivariate analysis theory and practice for statistics majors as well as nonmajors with little or no background in theoretical statistics. Among the many special features of this extremely accessible first text on multivariate analysis are:
* Clear, stepbystep explanations of all key concepts and procedures along with original, easytofollow proofs
* Numerous problems, examples, and tables of distributions
* Many realworld 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 indepth 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 standalone introduction or in concert with its more methodsoriented sibling volume, the critically acclaimed Methods of Multivariate Analysis.
Multivariate Statistical Inference and Applications is a userfriendly introduction to basic multivariate analysis theory and practice for statistics majors as well as nonmajors with little or no background in theoretical statistics. Among the many special features of this extremely accessible first text on multivariate analysis are:
* Clear, stepbystep explanations of all key concepts and procedures along with original, easytofollow proofs
* Numerous problems, examples, and tables of distributions
* Many realworld 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 indepth 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 standalone introduction or in concert with its more methodsoriented sibling volume, the critically acclaimed Methods of Multivariate Analysis.
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Some Properties of Random Vectors and Matrices.
The Multivariate Normal Distribution.
Hotelling's TēTests.
Multivariate Analysis of Variance.
Discriminant Functions for Descriptive Group Separation.
Classification of Observations into Groups.
Multivariate Regression.
Canonical Correlation.
Principal Component Analysis.
Factor Analysis.
Appendices.
Bibliography.
Index.
The Multivariate Normal Distribution.
Hotelling's TēTests.
Multivariate Analysis of Variance.
Discriminant Functions for Descriptive Group Separation.
Classification of Observations into Groups.
Multivariate Regression.
Canonical Correlation.
Principal Component Analysis.
Factor Analysis.
Appendices.
Bibliography.
Index.
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ALVIN 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.
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