內容簡介

  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.
 

作者介紹

作者簡介

Joseph F. Hair, Jr.


  現職:University of South Alabama

William C. Black

  現職:Louisiana State University

Barry J. Babin

  現職:Louisiana Tech University

Rolph E. Anderson

  現職:Drexel University
 

目錄

Ch 1 Overview of Multivariate Methods
 
SECTION I: PREPARING FOR MULTIVARIATE ANALYSIS

Ch 2 Examining Your Data

SECTION II: INTERDEPENDENCE TECHNIQUES
Ch 3 Exploratory Factor Analysis
Ch 4 Cluster Analysis

SECTION III: DEPENDENCE TECHNIQUES-METRIC OUTCOMES
Ch 5 Multiple Regression Analysis
Ch 6 MANOVA: Extending ANOVA

SECTION IV: DEPENDENCE TECHNIQUES-NON-METRIC OUTCOMES
Ch 7 Multiple Discriminant Analysis
Ch 8 Logistic Regression: Regression with a Binary Dependent Variable

SECTION V: MOVING BEYOND THE BASICS
Ch 9 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)
 
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