Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

We’ll use data taken from a Pew Research Center 2016 post-election survey, and you can download the dataset for your own use here. We’ll discuss both bivariate regression, which has one outcome ...

The R package rcssci offers an intuitive solution for visualizing Restricted Cubic Splines (RCS) in regression analyses. It automates the generation of spline plots for outcomes like odds ratios (OR), ...

The Statistics and Data Science curriculum links faculty and students from across the college interested in learning things from data. One important goal is to prepare students for careers in data ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

Specialization: Statistical Modeling for Data Science Applications Instructor: Brian Zaharatos, Director, Professional Master’s Degree in Applied Mathematics Prior knowledge needed: Basic calculus ...

Added-variable plots are useful for a variety of data-analytic purposes but can be seriously misleading when used to investigate curvature and predictor transformations in linear regression, unless ...