I taught this for the first time in Spring 2024. Students finished the course with a final project, analyzing a state/map of their choice. Here is some sample student work:
North Carolina 2022 and 2023 Congressional Redistricting Map Analysis, by Qianru Wei and Mingda Ma
North Dakota Redistricting Analysis by Kushal Chekuri and Pedro Pinheiro
Here is an outline of the topics:
Intro, Shape and population
Include graphs and dual graphs
Metrics: eg, mean median, geo
Markov Chains and outlier analysis
What are MCs
MCs in redistricting: flip, recom
Theory of MCs
Data wrangling
Ecological Inference
Short bursts
With finding VRA districts
With testing metrics
Extra topics (for example: GEO metric, Declination, the redistricting metagraph, machine learning to measure district compactness . . . )
Project work