Multivariate Statistical Inference and Applications

Alvin C. Rencher (Author)

9780471571513, Wiley

Multiple-component retail product, part(s) enclosed, published 9 January 1998

592 pages
24.2 x 16.4 x 3.5 cm, 1.034 kg

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.

Introduction

Matrix Algebra

Characterizing and Displaying Multivariate Data

The Multivariate Normal Distribution

Multivariate Analysis of Variance

Discriminant Analysis: Description of Group Separation

Classification of Analysis: Allocation of Observations to Groups

Multivariate Regression: Canonical Correlation

Principal Component Analysis

Factor Analysis

Appendices.

Subject Areas: Mathematics [PB]