Introduction to Statistical Modeling is a little different from the typical intro statistics class because it emphasizes modeling. While many introductory classes cover simple linear regression near the end of the course, Intro to Statistical Modeling exposes students to regression much earlier in the semester. Students in this class learn to visualize data; create, interpret, and test multiple linear regression models with and without interaction terms; and communicate their results to an audience with limited statistical experience. All work is done in R.

Students apply their statistical tools through a semester-long group project. In this project, they pose a research question on any topic that interests them; gather gather and organize their data; produce numerical summaries and visualizations of their data; produce regressions with multiple predictors; formally test their research question; and write a report to explain and conclude their work. The project also requires peer editing and revisions, giving students the opportunity to critically assess others’ work and improve upon their own work.

Click here for the group project details.

Click here for the course syllabus.

Click here to join the waitlist for 155 in the upcoming semester.