"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count data. The most ...

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 ...

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population ...

The goal of a binary classification problem is to make a prediction that can be one of just two possible values. For example, you might want to predict the sex (male or female) of a person based on ...

The slope and intercepts we compute in a regression model are statistics calculated from the sample data. They are point estimates of corresponding parameters; namely, the slope and intercept in the ...

Dr. James McCaffrey of Microsoft Research uses a full-code, step-by-step demo to show how to predict the annual income of a person based on their sex, age, state where they live and political leaning.