class: center, middle, inverse, title-slide .title[ # 1: Introduction ] .subtitle[ ## Linear Models ] .author[ ### <large>Jaye Seawright</large> ] .institute[ ### <small>Northwestern Political Science</small> ] .date[ ### Jan. 5, 2026 ] --- class: center, middle <style type="text/css"> pre { max-height: 400px; overflow-y: auto; } pre[class] { max-height: 200px; } </style> ### Goals This course is about linear models (regression), which involve a set of techniques that show up across nearly all areas of statistics. Regression models are used as a powerful tool to describe data, have value for forecasting, and are sometimes pressed into service for work in theory-testing and causal inference. Across these use cases, linear models are everywhere in political science. --- We will talk about: * regression as a tool for data summary * generalization and significance tests * common graphical displays * key assumptions available tests * interpreting results * when/if regression can speak to causal questions --- Grades will be based on weekly problem sets (30% total), three in-class quizzes (30% total), and a final summative problem set (40% total). Problem sets will combine explorations of conceptual understanding, some mathematical analysis, and computer work (with and without real-world data). For the weekly problem sets, students are welcome to form study groups and work together but must complete and submit their own work. For quizzes and the final summative problem set, the expectation is that each person will work alone. --- *Regression and Other Stories*, by Andrew Gelman, Jennifer Hill, and Aki Vehtar *A User’s Guide to Statistical Inference and Regression* by Matthew Blackwell --- ### Statistical Computing Throughout the quarter, we'll do a lot of work with simulation and data. It's easiest to do this in R. --- In addition to installing R and R Studio (and updating things), I recommend the following: ``` r install.packages("tidyverse") install.packages("remotes") remotes::install_github("avehtari/ROS-Examples",subdir = "rpackage") install.packages("modelsummary") ``` --- ### Benchmark Quiz Please take the course [benchmark quiz](https://canvas.northwestern.edu/courses/245562/quizzes/282337).