Applied Multivariate Statistical Analysis [Hardcover]

Richard Arnold Johnson (Author), Dean W. Wichern (Author)

Book Description

ISBN-10: 013834194X | ISBN-13: 978-0138341947 | Publication Date: July 13, 1998 | Edition: 4 Har/Dsk

This market leading text is appropriate for courses that teach statistical methods for describing and analyzing multivariate data in depts. of statistics, math, marketing, and in the biological, physical, and social sciences. The 4th edition makes more extensive use of SAS and SPSS output with an emphasis on interpretation. Features include additional exercises, data sets, and graphics to illustrate points. Various techniques such as MANOVA and Discriminate Analysis, Correspondence Analysis, and Biplots are integrated more thoroughly.

Editorial Reviews

From the Publisher

A classic applied approach to multivariate analysis for those involved in the social, biological, and physical sciences. --This text refers to an out of print or unavailable edition of this title.

From the Back Cover

Explores the statistical methods for describing and analyzing multivariate data. It's goal is to provide readers with the knowledge necessary to make proper interpretations, and select appropriate techniques for analyzing multivariate data Coverage includes: Detecting Outliers and Data Cleaning; Multivariate Quality Control; Monitoring Quality with Principal Components; and Correspondence Analysis, Biplots, and Procrustes Analysis.

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Product Details

• Hardcover: 799 pages
• Publisher: Prentice Hall College Div; 4 Har/Dsk edition (July 13, 1998)
• Language: English
• ISBN-10: 013834194X
• ISBN-13: 978-0138341947
• Product Dimensions: 9.8 x 8 x 1.5 inches
• Shipping Weight: 3.2 pounds
• Average Customer Review: 3.4 out of 5 stars  See all reviews (28 customer reviews)
• Amazon Best Sellers Rank: #1,274,636 in Books (See Top 100 in Books)

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49 of 50 people found the following review helpful:

4.0 out of 5 stars Book Contents, March 10, 2006

By 

MAURICIO AGUIAR (Rio de Janeiro, RJ, Brazil) - See all my reviews
(REAL NAME)   

This review is from: Applied Multivariate Statistical Analysis (5th Edition) (Hardcover)

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.

43 of 44 people found the following review helpful:

5.0 out of 5 stars A Students Review, February 6, 2002

By 

Hrafn (Denver, CO) - See all my reviews

This review is from: Applied Multivariate Statistical Analysis (Hardcover)

First: I must prefix this by saying that I am majoring in the Mathematical and Computer Sciences.

This semester I decided to take a class that happened to use this text as its source. I have been extremely pleased with it: the theoretical work is excellent, the proofs are thourough, the exercises are both good and cover a broad variety of difficulties, and the tables on the CD provide excellent experience in analyzing real world data.

A couple of things to keep in mind before you purchase this book, however:

1) A good background in linear algebra and basic statistics is highly recommended and virtually necessary to interpret this book. Remembering the knowledge gleaned from "Sequences and Series" (often taught in Calculus II) will also prove useful. The text is good, but it is often nontrivial.

2) Some kind of software that does multivariate analysis (and if nothing else, will find eigenvalues and orthonormal eigenvectors) is necessary to get the most out of this book. The software package SAS is touched on in the book, but by no means is given a comprehensive review. However, the data files on the CD-ROM should be loadable by any competant software package, so use the one you are most comfortable with.

If not overly familiar with any of them, I can recommend S, SPlus, and "GNU's S" (also known as "R") for their power and flexability to work with the data presented in the book.

All and all I found this to be an excellent book, definantly worthwhile if you want or need to know how to do multivariate analysis.

32 of 34 people found the following review helpful:

4.0 out of 5 stars excellent book, February 12, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Applied Multivariate Statistical Analysis (Hardcover)

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.