Logistic regression analysis is a popular technique for classifying individuals into two classes, effectively, modelling a binary class variable. In direct marketing, response (to a prior solicitation) is the binary class variable (defined by responders and nonresponders), and the logistic regression model is built to classify an individual as either most-likely or least-likely to respond to a future solicitation.

This article provides a brief overview of logistic regression and the SAS-code  program for building and scoring a logistic regression model, which should be a welcomed entry in the tool kit of data analysts who frequently work on the two-group classification problem.