Binomial means two. Let’s review. Logistic regression is a technique that models a categorical dependent variable Y based on one or more independent variables X. The dependent variable can have two or more possible discrete values. This post is on binomial logistic regression, which models the probability of an observation falling into one of two categories based on one or more independent variables.

Logistic regression is a technique that models a categorical dependent variable Y based on one or more independent variables X. The dependent variable can have two or more possible discrete values. Here we’ll look at binomial logistic regression, which models the probability of an observation falling into one of two categories based on one or more independent variables. We use a binary variable Y to indicate the category.

What questions can you ask? How likely is it that a person will do something? In sports, that something could be scoring a certain number of points or gaining a certain number of yards in American football. It could be the likelihood of someone leaving the company as a customer, such as bank churn.

Examples

How likely is it that a basketball player will score 12 or more points in a game? Will a student get 70% or above on their final exam, yes or no? Predicting whether employees are likely to stay with or leave a company based on the number of years with the company. Will a product fail within it’s first year under the warrantee?

Below is the formula for the logistic function. I used latex to display this on this page.

Here’s what it looks like graphed on the x and y coordinate plane, from the website GeoGebra.org. GeoGebra is set of free tools to do math. It’s a platform to connect enthusiastic teachers and students and offer them a new way to explore and learn about math.