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For graduate and upper-level undergraduate marketing research courses.
For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis.
Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques.
In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.
Table of ContentsI Introduction
II Preparing For a MV Analysis
2 Examining Your Data
3 Factor Analysis
III Dependence Techniques
4 Multiple Regression Analysis
5 Multiple Discriminate Analysis and Logistic Regression
6 Multivariate Analysis of Variance
7 Conjoint Analysis
IV Interdependence Techniques
8 Cluster Analysis
9 Multidimensional Scaling and Correspondence Analysis
V Moving Beyond the Basic Techniques
10 Structural Equation Modeling: Overview
10a Appendix – SEM
11 CFA: Confirmatory Factor Analysis
11a Appendix – CFA
12 SEM: Testing A Structural Model
12a Appendix – SEM
A Basic Stats