In this course, students will learn data science using the statistical programming language R, with a focus on political science applications. By the end of the course, students will be able to work with large datasets, build beautiful visualizations, make predictions, and conduct statistical analyses.
Athena Title
Political Analysis in R
Prerequisite
POLS 1101 or POLS 1101E or POLS 1101H or POLS 1101S
Grading System
A - F (Traditional)
Student learning Outcomes
Students will be able to understand the basics of computer programming using R as a learning platform.
Students will be able to manage large, messy political datasets using the tools in R's tidyverse package.
Students will be able to create striking, informative visualizations of political data using R's ggplot2 package.
Topical Outline
Part 1: Exploration
Week 1: Programming Basics
Week 2-3: Visualizing Data
Week 4: Data Wrangling (Importing, Tidying, and Statistical Transformations)
Part 2: Prediction
Week 5: Linear Models
Week 6-7: Machine Learning
Week 8: Prediction Competition
Part 3: Uncertainty
Week 9-10: Probability
Week 11: Estimation
Week 12: Confidence Intervals
