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Applied Multivariate Statistical Analysis (5th Edition)

by Richard A. Johnson, Dean W. Wichern

ISBN-10: 9780130925534
ISBN-10: 0-13-092553-5
ISBN-13: 9780130925534
ISBN-13: 978-0-13-092553-4
Hardcover
2001-12-06
Prentice Hall


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Editorials


Product Description

This market-leading book offers a readable introduction to the statistical analysis of multivariate observations. Its overarching goal is to provide readers with the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Chapter topics include aspects of multivariate analysis, matrix algebra and random vectors, sample geometry and random sampling, the multivariate normal distribution, inferences about a mean vector, comparisons of several multivariate means, multivariate linear regression models, principal components, factor analysis and inference for structured covariance matrices, canonical correlation analysis, and discrimination and classification. For experimental scientists in a variety of disciplines.


Reviews


excellent book
There have been many good theoretical texts on multivariate analysis including Anderson, Eaton and Gnandesikan. Tabachnick has written a popular applied text for the social sciences. Yet for many years this has been considered the best applied text. That is because the authors understand the theory and know how to balance it with applications. They also are excellent writers.

Non Fiction
Applied Multivariate Statistical Analysis
by Richard A. Johnson is your basic beyond basic if you will, garden variety big honking textbook deal.

A somewhat useful tome, but again, not that particularly interesting or great otherwise, other than being a text. These things can certainly be done better.

Not as Applied as I Hoped
While this text covers a variety of multivariate techniques, the term "applied" is used loosely, in my opinion.

This is more a math-stat textbook than an applied statistics text.

I wish I had read the reviews (if they existed when I purchased the 4th edition), for I would have purchased a different text.

NOT a good intro to MVA
My prof used this book for multivariate statisitical analysis. I absolutely despise this book. For one, the answers to exercises come in a separate book, so the homework questions are worthless to me. The solutions will cost you an extra $100 or so if you buy that book. The index is extremely light, so if you want a quick reference to a topic - forget it. You'll need to skim through hundereds of pages that aren't referenced in the index. Important topics are illustrated in 1 example usually, and the reader is often left to guess how such problems could be adapted to different situations than what is illustrated.

Book Contents
The "search inside this book" feature was not available when this review was posted. Hope it helps.

CONTENTS

I. GETTING STARTED.
1. Aspects of Multivariate Analysis.
2. Matrix Algebra and Random Vectors.
3. Sample Geometry and Random Sampling.
4. The Multivariate Normal Distribution.
II. INFERENCES ABOUT MULTIVARIATE MEANS AND LINEAR MODELS.
5. Inferences About a Mean Vector.
6. Comparisons of Several Multivariate Means.
7. Multivariate Linear Regression Models.
III. ANALYSIS OF A COVARIANCE STRUCTURE.
8. Principal Components.
9. Factor Analysis and Inference for Structured Covariance Matrices.
10. Canonical Correlation Analysis
IV. CLASSIFICATION AND GROUPING TECHNIQUES.
11. Discrimination and Classification.
12. Clustering, Distance Methods and Ordination.
Appendix.
Data Index.
Subject Index.


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