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Course Description

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UW Statistics

UW CSSS

UW Philosophy

TA: TBA

Brief description
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 3 will be chosen to be directly related to the 2020 US election. See more here and in the list of topics (t.b. updated)

Canvas course site here (t.b. published)

Prerequisites

• STAT 498 STAT 311 or STAT 390 or STAT 391 or CSE 312
• CSSS 594 Graduate-level introductory sequence in applied statistics such as SOC 504-505-506 or equivalent
• STAT 498/CSSS 594 It is highly recommended that students have some familiarity with reading and writing proofs, have taken at least an introductory statistics course, and have beginner ability with data programming.