# Applied Multivariate Analysis

• Neil H. Timm
Textbook

Part of the Springer Texts in Statistics book series (STS)

1. Front Matter
Pages i-xxiv
2. Pages 1-5
3. Pages 7-78
4. Pages 79-184
5. Pages 185-309
6. Pages 311-349
7. Pages 351-417
8. Pages 419-443
9. Pages 515-555
10. Pages 557-607
11. Back Matter
Pages 609-693

### Introduction

Univariate statistical analysis is concerned with techniques for the analysis of a single random variable. This book is about applied multivariate analysis. It was written to p- vide students and researchers with an introduction to statistical techniques for the ana- sis of continuous quantitative measurements on several random variables simultaneously. While quantitative measurements may be obtained from any population, the material in this text is primarily concerned with techniques useful for the analysis of continuous obser- tions from multivariate normal populations with linear structure. While several multivariate methods are extensions of univariate procedures, a unique feature of multivariate data an- ysis techniques is their ability to control experimental error at an exact nominal level and to provide information on the covariance structure of the data. These features tend to enhance statistical inference, making multivariate data analysis superior to univariate analysis. While in a previous edition of my textbook on multivariate analysis, I tried to precede a multivariate method with a corresponding univariate procedure when applicable, I have not taken this approach here. Instead, it is assumed that the reader has taken basic courses in multiple linear regression, analysis of variance, and experimental design. While students may be familiar with vector spaces and matrices, important results essential to multivariate analysis are reviewed in Chapter 2. I have avoided the use of calculus in this text.

### Keywords

Analysis of variance Cluster analysis Factor analysis SAS analysis data analysis multidimensional scaling principal component analysis structural equation modeling

### Editors and affiliations

• Neil H. Timm
• 1
1. 1.Department of Education in Psychology School of EducationUniversity of PittsburghPittsburgh

### Bibliographic information

• DOI https://doi.org/10.1007/b98963
• Copyright Information Springer-Verlag New York, Inc. 2002
• Publisher Name Springer, New York, NY
• eBook Packages
• Print ISBN 978-0-387-95347-2
• Online ISBN 978-0-387-22771-9
• Series Print ISSN 1431-875X
• Buy this book on publisher's site