The linear model is one of the most commonly-used statistical models. Also called the regression model or the ordinary linear regression, linear modeling is the foundation for more complex general linear models like logit or count models, mixed-effects models, and structural equation models. So it's a good model to understand. This workshop will cover to use R to fit and analyze linear models. Through hands-on examples, we'll talk about interpetation of model output and checking model assumptions. We'll also explore dummy variables, interactions, and variable transformations. While the workshop will assume you've met a regression model before, it can serve as a refresher for forgotten statistics! This workshop also assumes basic experience using R and familiarity with the tidyverse libraries, or successful completion of our Intro to R, Data Preparation in R, and Data Visualization in R workshops.