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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 students how to understand and make use of the results of specific statistical techniques.
In this seventh revision, 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.
NEW! Chapter Reorganization: Chapters now focus on a single topic and begin with providing basic information and application techniques. This is followed by more in-depth discussions later in the chapter.
NEW! “Rule of Thumb” Feature Expanded: This feature has been improved so students learn how to best use different techniques.
Use of Technical Terms and Statistical Notation Minimized: In order to make the text more accessible to management and non-mathematically focused students, the authors explain complex techniques in everyday language.
Ch 1 Overview of Multivariate Methods
Ch 2 Examining Your Data
Ch 3 Exploratory Factor Analysis
Ch 4 Multiple Regression Analysis
Ch 5 Multiple Discriminant Analysis
Ch 6 Logistic Regression: Regression with a Binary Dependent Variable
Ch 7 Conjoint Analysis
Ch 8 Cluster Analysis
Ch 9 Multidimensional Scaling
Ch10 Analyzing Nominal Data with Correspondence Analysis
Ch11 Structural Equations Modeling Overview
Ch12 Confirmatory Factor Analysis
Ch13 Testing Structural Equations Models
