
Multivariate Statistical Inference and Applications
Alvin C. Rencher(Author)
Wiley (Publisher)
Published on 9. January 1998
Book
Hardback
592 pages
978-0-471-57151-3 (ISBN)
Description
The 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 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, 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.
More details
Product info
Book with Disk 3.5
Series
Edition
1. Auflage
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
College/higher education
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 36 mm
Weight
1044 gr
ISBN-13
978-0-471-57151-3 (9780471571513)
Schweitzer Classification
Person
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.
Content
Some Properties of Random Vectors and Matrices.
The Multivariate Normal Distribution.
Hotelling's T²-Tests.
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.