Multivariate data analysis
Author(s)
Bibliographic Information
Multivariate data analysis
Pearson Prentice Hall, Pearson Education International, c2006
6th ed., Pearson international edition
- [: pbk]
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Note
Other authors: William C. Black, Barry J. Babin, Rolph E. Anderson, Ronald L. Tatham
Includes bibliographical references and index
Created due to the difference in publication year
Description and Table of Contents
Description
For graduate-level courses in Marketing Research, Research Design and Data Analysis.
Multivariate Data Analysis provides an applications-oriented introduction to multivariate data analysis for the nonstatistician by focusing on the fundamental concepts that affect the use of specific techniques.
Table of Contents
Chapter 1: IntroductionChapter 2: Examining Your Data
Chapter 3: Factor Analysis
Chapter 4: Regression
Chapter 5: Multiple Discriminant Analysis
Chapter 6: Manova
Chapter 7: Conjoint Analysis
Chapter 8: Cluster Analysis
Chapter 9: MDS
Chapter 10: Structural Equation Modeling: An Introduction
Chapter 11: SEM: Confirmatory Factor Analysis
Chapter 12: SEM: Testing A Structural Model
by "Nielsen BookData"
