For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. 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 todays 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.
Chapter 1 Overview of Multivariate Methods Section 1: Preparing for Multivariate Analysis Chapter 2: Examining Your Data Section 2: Interdependence Techniques Chapter 3: Exploratory Factor Analysis Chapter 4: Cluster Analysis Section 3: Dependence Techniques Chapter 5: Multiple Regression Chapter 6: MANOVA: Extending ANOVA Chapter 7: Discriminant Analysis Chapter 8: Logistic Regression: Regression with a Binary Dependent Variable Section 4: Moving Beyond the Basic Techniques Chapter 9: Structural Equation Modeling: An Introduction Chapter 10: Confirmatory Factor Analysis Chapter 11: Testing Structural Equation Models Chapter 12: Advanced Topics in SEM Chapter 13: Partial Least Squares Modeling (PLS-SEM) In addition to the chapters in the print book, e-copies of all other chapters in the previous editions are available to download on the companion website, including canonical correlation, conjoint analysis, multidimensional scaling, and correspondence analysis.
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