The eighth edition of Multivariate Data Analysis provides an updated perspective on the analysis of all types of data as well as introducing some new perspectives and techniques that are foundational in today’s world of analytics. Multivariate Data Analysis serves as the perfect companion for graduate and postgraduate students undertaking statistical analysis for business degrees, providing an application-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques.
Ch1 Overview of Multivariate Methods
SECTION I: PREPARING FOR MULTIVARIATE ANALYSIS
Ch2 Examining Your Data
SECTION II: INTERDEPENDENCE TECHNIQUES
Ch3 Exploratory Factor Analysis
Ch4 Cluster Analysis
SECTION III: DEPENDENCE TECHNIQUES-METRIC OUTCOMES
Ch5 Multiple Regression Analysis
Ch6 MANOVA: Extending ANOVA
SECTION IV: DEPENDENCE TECHNIQUES-NON-METRIC OUTCOMES
Ch7 Multiple Discriminant Analysis
Ch8 Logistic Regression: Regression with a Binary Dependent Variable
SECTION V: MOVING BEYOND THE BASICS
Ch9 Structural Equation Modeling: An Introduction
Ch10 SEM: Confirmatory Factor Analysis
Ch11 Testing Structural Equation Models
Ch12 Advanced SEM Topics
Ch13 Partial Least Squares Structural Equation Modeling (PLS-SEM)
作者：Joseph F. Hair, Jr.
現職：University of South Alabama
作者：William C. Black
現職：Louisiana State University
作者：Barry J. Babin
現職：Louisiana Tech University
作者：Rolph E. Anderson
現職：Drexel University