Courses

Multivariate Data Analysis for Decision Making

18 Hours

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Learning Objectives

Learning Objectives

This course addresses two statistical techniques commonly used in the corporate environment to support decision-making. Firstly, logistics regression, which describes the behavior of a binary variable (e.g., separating solvent from insolvent companies) and independent variables (e.g., economic-financial indicators of solvent and insolvent companies) to investigate the effect of variables that individuals and objects are subject to regarding the likelihood of a certain event of interest (e.g., a manager interested in assessing the likelihood of a retail customer’s insolvency given its sociodemographic or financial features of income, age, civil status, etc.). Secondly, we will discuss cluster analysis, an exploratory method that gathers observations, individuals or variables as per significantly similar characteristics (e.g., a company may use this technique for customer or investment segmentation and assess possible market niches until then unexplored).

Program content

Logistics Regression − Introduction

Logistics Regression – Applications

Cluster Analysis − Introduction

Cluster Analysis − Application

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