Logistic Regression: A Step by Step Solution Using Microsoft Excel

Abstract

While knowledge of statistical and predictive analytical software is valued by the business community, it is assumed that business students have had extensive hands-on experience with Microsoft Excel and can be immediately productive with spreadsheets when walking in for their first day of work! This tutorial provides additional Microsoft Excels skills by showing how to create a logistic regression classification model, used in many business fields, from an intuitive perspective. The Solver nonlinear optimization Microsoft Excel add-in is used to derive the maximum likelihood estimates of the model coefficients. Model validation and performance are also completed with Microsoft Excel. Students are exposed to a wider view of optimization, and why it is at the heart of most machine learning algorithms. Student learning assessments from undergraduate and graduate classes are included to support our findings.