Multivariate Analysis 3e

By Alvin C. Rencher and William F. Christensen

Book Overview

Praise for the Second Edition

"This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."
--IIE Transactions

Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life situations.

This Third Edition continues to explore the key descriptive and inferential procedures that result from multivariate analysis. Following a brief overview of the topic, the book goes on to review the fundamentals of matrix algebra, sampling from multivariate populations, and the extension of common univariate statistical procedures (including t-tests, analysis of variance, and multiple regression) to analogous multivariate techniques that involve several dependent variables. The latter half of the book describes statistical tools that are uniquely multivariate in nature, including procedures for discriminating among groups, characterizing low-dimensional latent structure in high-dimensional data, identifying clusters in data, and graphically illustrating relationships in low-dimensional space. In addition, the authors explore a wealth of newly added topics, including:

Confirmatory Factor Analysis Classification Trees Dynamic Graphics Transformations to Normality Prediction for Multivariate Multiple Regression Kronecker Products and Vec Notation

New exercises have been added throughout the book, allowing readers to test their comprehension of the presented material. Detailed appendices provide partial solutions as well as supplemental tables, and an accompanying FTP site features the book's data sets and related SAS(R) code.

Requiring only a basic background in statistics, Methods of Multivariate Analysis, Third Edition is an excellent book for courses on multivariate analysis and applied statistics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for both statisticians and researchers across a wide variety of disciplines.

• Format: Hardcover
• Language: English
• ISBN: 0470178965
• ISBN13: 9780470178966
• Release Date: July 2012
• Publisher: Wiley
• Length: 800 Pages
• Weight: 2.60 lbs.
• Dimensions: 1.8" x 6.1" x 9.3"

Customer Reviews

Rencher writes very well

This is a clearly written text on multivariate analysis. As there are many excellent texts both involving theory and applications, using geometric approaches as in Eaton's biik and algebraic approaches as in Anderson's it is important to know the differences and the avanatges and disadvantages to each. Rencher's book has a lot of good applications and is very applications oriented in its approach. It does not cover structural equation models. The field of multivariate statistics is very broad and topics such as classification (or pattern recognition), structural equation models and factor analysis are often better understood by reading specialized texts such as McLachlan for pattern recognition, Bollen for structural equations and Harman for factor analysis. Rencher's book is modern, well-written and very much up to date.

Multivariate analysis book

The book was brand new. It arrived to me in perfect conditions although having been travelled from USA to Europe. The shipment was fast and cheap. I will repeat. Thanks!

good business

exactly what it says on the cover, good dealer, do recommend (the seller) hte book s good too, however multivariate analysis is not easy...

concise and clear

This textbook provides a comprehensive introduction to multivariate analysis. Although concise, the explanation is clear and intuitive, of course, some preliminary knowledge of statistics and linear algabra is necessary to follow this book.

Very Helpful!

This book is great! Some derivations and occasional proofs are included in the text, but it has clearly been written with the applied researcher in mind. In the author's words he has provided "careful intuitive explanations of the concepts and [has] included many insights typically available only in journal articles or in the minds of practitioners" with his primary objective being "clarity of exposition." I have found it to be very easy to read with numerous helpful examples (the data sets and SAS command files for which are available via an ftp site). This brand new version includes new chapters on cluster analysis, multidimensional scaling, correspondence analysis, and biplots.