The purpose of statistical model selection is to identify a parsimonious model, which is a model that is as simple as possible while maintaining good predictive ability over the outcome of interest.

Looking to get into statistical programming but lack industry experience? We spoke with several statistical programmers from diverse backgrounds, and one thing became clear—there’s no single path to ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

R is a powerful open source programming environment primarily known for its statistical capabilities. In this course we will cover some advanced applications of R: distributed computing using the ...

Additive models and tree-based regression models are two main classes of statistical models used to predict the scores on a continuous response variable. It is known that additive models become very ...

If a defensive coordinator of a National Football League team could predict with high accuracy whether their team's opponent will call a pass or run play during a game, he would become a rock star in ...

A statistical model -- now an easy-to-use software tool -- local police can use to identify a series of related crimes and nab a suspect has been unveiled. Crime linkage is the investigative process ...