Marketing Research, 11th Edition

CHAPTER 18Multivariate Data Analysis

LEARNING OBJECTIVES

1. Define multivariate data analysis.
2. Gain insights into multivariate software.
3. Describe Multiple Discriminant Analysis.
4. Understand cluster analysis.
5. Understand factor analysis.

This chapter continues our review of methods for data analysis, ways and tools that we can use to get data to give up the insights that we are seeking and that will enable us to make better decisions. The tools we will discuss in this chapter are parsimonious in output but huge in insight. Just a few statistics from each tool give us the direction we need. Used properly, these tools are very efficient and powerful.

Multivariate Analysis Procedures

The term multivariate analysis refers to the simultaneous analysis of multiple measurements on each individual or object being studied.¹ Some experts consider any simultaneous statistical analysis of more than two variables to be multivariate analysis. Multivariate analysis procedures are extensions of the univariate and bivariate statistical procedures discussed in Chapters 16 and 17.

multivariate analysis

A general term for statistical procedures that simultaneously analyze multiple measurements on each individual or object under study.

A number of techniques fall under the heading of multivariate analysis procedures. In this chapter, we will consider five of these techniques:

• Multiple regression analysis ...