Data Science for Business and Decision Making

Introduction

Two or more variables can relate to one another in several different ways. While one researcher may be interested in the study of the interrelationship between categorical (or nonmetric) variables, for example, in order to assess the existence of possible associations between its categories, another researcher may wish to create performance indicators (new variables) from the existence of correlations between the original metric variables. A third researcher may be interested in identifying homogeneous groups possibly formed from the existence of similarities in the variables between the observations of a certain dataset. In all of these situations, researchers may use multivariate exploratory techniques.

Multivariate exploratory ...