Multivariate Data Analysis

For graduate and upper-level undergraduate marketing research courses.

For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.

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.

1 Introduction: Models and Model Building

Section I Understanding and Preparing for Multivariate Analysis

2 Cleaning and Transforming Data
3 Factor Analysis

Section II Analysis Using Dependece Techniques
4 Simple and Multiple Regression Analysis
5 Canonical correlation

6 Conjoint analysis
7 Multiple Discriminant Analysis and Logistic Regression

8 ANOVA and MANOVA

Section III Analysis using Interdependence Techniques

9 Group data and Cluster Analysis
10 MDS and Correspondence Analysis

Structural Equation Modeling

11 SEM: An Introduction

12 Application of SEM

For graduate and upper-level undergraduate marketing research courses.

For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.

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.

NEW! Additional Chapters: Structural Equations Modeling has been expanded and reorganized, now covering 4 chapters.

Other topics of distinction

NEW! Expansion of Website: “Great Ideas in Teaching Multivariate” Statistics has been updated to provide even more links for students and resources for instructors. There are a number of teaching materials available, including exercises, datasheets, and project ideas. The website can be found at www.mvstats.com