Course description(t.b. updated) This course will consider a number of topics that are relevant to modern voting and elections through statistical and social choice lenses. The course will be co-taught by Elena Erosheva (Statistics and Social Work), Conor Mayo-Wilson (Philosophy), and Marina Meila (Statistics), and will also feature a number of expert guest speakers. Topics include the purpose and limits of democratic decision-making; majority rule, social choice theory and the associated impossibility theorems; judgement aggregation; probabilistic pooling; majority judgement and other voting procedures; election case studies; election polling and forecasting; misinformation and elections; electoral redistricting and gerrymandering; fairness aspects in voting, voting in contexts other than elections. Topics before and around November 8 will be chosen to be directly related to the 2022 US election. Course assessments will include participation in class and in discussion boards and hands-on homework assignments that will involve analyzing real or simulated data. Final grades will be based on participation (40% for undergraduate and 20% for graduate students), homework (60% for undergraduate and 40% for graduate students) and final paper (40%) for graduate students. Prerequisites
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