Question

Dependence and Interdependence are two very important words for leaders to know, consider, understand, and be able to practice in reality. For this discussion, describe the distinction between dependence and interdependence multivariate techniques. Provide a description of each and how each would apple in a real life scenario. What are your thoughts on each?

Answer 1

Dependence and Interdependence are two major classifications of the multivariate data analysis techniques. Multivariate techniques come into play when there exist simultaneous relationships among two or more variables. This is very relevant in marketing research, personalization, campaigns as majority of the business problems are multidimensional.

In Dependence method, one or more of the variables are identified as dependent and these can be predicted or explained by the remaining independent variables. Examples of this include regression, discriminant analysis and conjoint analysis. Real life example can be to predict customer mobile data usage basis their age, income group, lifestyle, location etc.

An Interdependence model is one in which no one variable or set of variables are defined being either dependent or independent. The goal here is to reduce or group data to analyze further. This simplifies the data and groups things together. Factor analysis, Cluster analysis, perceptual mapping and multidimensional scaling are some of the interdependence techniques. Real life examples include clustering approach for personalization marketing or personalization user interfaces (UI) used by e-commerce companies.