Principal Components Analysis
May 1989 | 96 pages | Sage US
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Paperback
ISBN: 9780803931046
Available from January 0001

Description

For anyone in need of a concise, introductory guide to principle 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. In addition, the author shows how this technique can be used in tandem with other multivariate analysis techniques-such as multiple regression and discriminant analysis.

Flexible in his presentation, Dunteman speaks to students at differing levels, beginning or advanced, bringing them new material that is both accessible and useful.

"Two of the best attributes of the book are the prolific use of good examples--primarily social science based--and the repetition basics. . . . This book is a useful addition to the work in this area."

--Issues in Researching Sexual Behavior

"Most academic researchers and practitioners will benefit from the experience and practical advice in this paper. Not only does Dunteman contribute to our understanding of principal components, but he suggests several good ideas on how to make wider and better use of the technique."

--Journal of Marketing Research

"A concise, introductory guide with a minimal use of matrix algebra and with multiple real-life examples."

--Bulletin de Methodologie Sociologique

"An interesting and useful little book."

--Journal of Classification

Learn more about "The Little Green Book" - QASS Series! Click Here


Contents

Introduction

Introduction

Basic Concepts of Principal Components

Basic Concepts of Principal Components

Geometrical Properties of Principal Components

Geometrical Properties of Principal Components

Decomposition Properties of Principal Components

Decomposition Properties of Principal Components

Principal Components of Patterned Correlation Matrices

Principal Components of Patterned Correlation Matrices

Rotation of Principal Components

Rotation of Principal Components

Using Principal Components to Select a Subset of Variables

Using Principal Components to Select a Subset of Variables

Principal Components Versus Factor Analysis

Principal Components Versus Factor Analysis

Uses of Principal Components in Regression Analysis

Uses of Principal Components in Regression Analysis

Using Principal Components to Detect Outlying and Influential Observations

Using Principal Components to Detect Outlying and Influential Observations

Use of Principal Components in Cluster Analysis

Use of Principal Components in Cluster Analysis

Use of Principal Components Analysis in Conjunction with Other Multivariate Analysis Procedures

Use of Principal Components Analysis in Conjunction with Other Multivariate Analysis Procedures

Other Techniques Related to Principal Components

Other Techniques Related to Principal Components

Summary and Conclusions

Summary and Conclusions

Description

For anyone in need of a concise, introductory guide to principle 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. In addition, the author shows how this technique can be used in tandem with other multivariate analysis techniques-such as multiple regression and discriminant analysis.

Flexible in his presentation, Dunteman speaks to students at differing levels, beginning or advanced, bringing them new material that is both accessible and useful.

"Two of the best attributes of the book are the prolific use of good examples--primarily social science based--and the repetition basics. . . . This book is a useful addition to the work in this area."

--Issues in Researching Sexual Behavior

"Most academic researchers and practitioners will benefit from the experience and practical advice in this paper. Not only does Dunteman contribute to our understanding of principal components, but he suggests several good ideas on how to make wider and better use of the technique."

--Journal of Marketing Research

"A concise, introductory guide with a minimal use of matrix algebra and with multiple real-life examples."

--Bulletin de Methodologie Sociologique

"An interesting and useful little book."

--Journal of Classification

Learn more about "The Little Green Book" - QASS Series! Click Here


Contents

Introduction

Introduction

Basic Concepts of Principal Components

Basic Concepts of Principal Components

Geometrical Properties of Principal Components

Geometrical Properties of Principal Components

Decomposition Properties of Principal Components

Decomposition Properties of Principal Components

Principal Components of Patterned Correlation Matrices

Principal Components of Patterned Correlation Matrices

Rotation of Principal Components

Rotation of Principal Components

Using Principal Components to Select a Subset of Variables

Using Principal Components to Select a Subset of Variables

Principal Components Versus Factor Analysis

Principal Components Versus Factor Analysis

Uses of Principal Components in Regression Analysis

Uses of Principal Components in Regression Analysis

Using Principal Components to Detect Outlying and Influential Observations

Using Principal Components to Detect Outlying and Influential Observations

Use of Principal Components in Cluster Analysis

Use of Principal Components in Cluster Analysis

Use of Principal Components Analysis in Conjunction with Other Multivariate Analysis Procedures

Use of Principal Components Analysis in Conjunction with Other Multivariate Analysis Procedures

Other Techniques Related to Principal Components

Other Techniques Related to Principal Components

Summary and Conclusions

Summary and Conclusions

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Principal Components Analysis


May 1989 | 96 pages | Sage US

Format Published Date ISBN Price
Paperback 28/02/2026 9780803931046 $55.00

For anyone in need of a concise, introductory guide to principle 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. In addition, the author shows how this technique can be used in tandem with other multivariate analysis techniques-such as multiple regression and discriminant analysis.

Flexible in his presentation, Dunteman speaks to students at differing levels, beginning or advanced, bringing them new material that is both accessible and useful.

"Two of the best attributes of the book are the prolific use of good examples--primarily social science based--and the repetition basics. . . . This book is a useful addition to the work in this area."

--Issues in Researching Sexual Behavior

"Most academic researchers and practitioners will benefit from the experience and practical advice in this paper. Not only does Dunteman contribute to our understanding of principal components, but he suggests several good ideas on how to make wider and better use of the technique."

--Journal of Marketing Research

"A concise, introductory guide with a minimal use of matrix algebra and with multiple real-life examples."

--Bulletin de Methodologie Sociologique

"An interesting and useful little book."

--Journal of Classification

Learn more about "The Little Green Book" - QASS Series! Click Here



Table Of Contents:

  • 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

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