Learn how to use logistic regression to predict the probability of a binary outcome based on explanatory variables, and understand the assumptions and interpretations of the model.

The quantity on the left is called the _log-odds_ or _logit_, and so logistic regression models the log-odds as a linear function of the predictor variable. The coefficients are chosen via the ...

The coefficients from the logistic regression model provide insight into how each predictor variable influences the likelihood of a positive outcome, such as a diabetes diagnosis.

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Dependent and Independent Variables Logistic regression models have one dependent variable and several independent categorical or continuous predictor variables. Unlike standard linear regression ...

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems.

Dr. James McCaffrey of Microsoft Research uses a full code program, examples and graphics to explain multi-class logistic regression, an extension technique that allows you to predict a class that can ...