Election Fundamentals and Forecasting

Undergraduate

This course examines the fundamental forces that determine election outcomes in the United States. Students practice data analytics using real election results and historical data, and ultimately build a predictive model of the 2024 U.S. election. After the election, students assess their model accuracy. Topics include but are not limited to: presidential approval, the economy, incumbency and candidate quality, campaign and media effects, partisan polarization, case studies of key presidential elections, and election regulations. Throughout the course we explore how the class material helps us understand the dynamics in the upcoming/ongoing 2024 election campaign. Instructor permission required. Students must have at least completed a class that teaches regression techniques (some examples include PLSC 347, 438, 452, the YData courses, Stat 230, or similar, etc.). Students should also have experience coding (the class will mainly use R). Weekly assignments involved coding and making election predictions using real world data. QR , SO 0 Course cr TTh 10:30am-11:20am