The goal is to understand why some have re-subscribed while others have not. These readers were asked to renew their subscription which is due to expire in two weeks. The data correspond to a sample of 60 readers, with the age category, the average number of page views per week over the last 10 weeks, and the number of page views during the last week. The example we consider below is a marketing scenario in which we try to predict the probability that a customer will renew his subscription to an online information service. Data set for running a binary logit model Logistic regression models the probability of an event occurring given the values of a set of quantitative and/or qualitative descriptive variables. With XLSTAT, it is possible to run logistic regression either directly on raw data (the answer is 0 or 1) or on aggregated data (the answer is a sum of successes - of 1 for example - and in this case the number of repetitions must also be available). one that can only take two values 0/1 or Yes/No for example.Ī logistic regression will be very useful to model the effect of doses of medication in medicine, doses of chemical components in agriculture, or to evaluate the propensity of customers to answer a mailing, or to measure the risk of a customer not paying back a loan in a bank. Logistic regression, and associated methods such as Probit analysis, are very useful when we want to understand or predict the effect of one or more variables on a binary response variable, i.e. Not sure this is the modeling feature you are looking for? Check out this guide.

This tutorial will help you set up and interpret a Logistic Regression in Excel using the XLSTAT software.

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