For anyone in need of a concise, introductory guide to principal components analysis, this book is a must. Through an effective use of simple mathematical-geometrical and multiple real-life examples (such as crime statistics, indicators of drug abuse, and educational expenditures) -- and by minimizing the use of matrix algebra -- the reader can quickly master and put this technique to immediate use.

Introduction
Basic Concepts of Principal Components
Geometrical Properties of Principal Components
Decomposition Properties of Principal Components
Principal Components of Patterned Correlation Matrices
Rotation of Principal Components
Using Principal Components to Select a Subset of Variables
Principal Components Versus Factor Analysis
Uses of Principal Components in Regression Analysis
Using Principal Components to Detect Outlying and Influential Observations
Use of Principal Components in Cluster Analysis
Use of Principal Components Analysis in Conjunction with Other Multivariate Analysis Procedures
Other Techniques Related to Principal Components
Summary and Conclusions