Description

Book Synopsis


Table of Contents
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.

Multivariate Data Analysis

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    A Paperback / softback by William Black, Joseph Hair, Rolph Anderson

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      Book details

      Publisher Cengage Learning EMEA
      Published 24 May 2018
      ISBN-13 9781473756540
      978-1473756540
      ISBN-10 1473756545
      Also in:
      Politics, Philosophy & Society Education / Educational sciences / Pedagogy

      Description

      Book Synopsis


      Table of Contents
      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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