mathbabe

This is a guest post by Ben Blum-Smith, a math teacher and researcher. You can find Ben on Twitter at @benblumsmith or read his blog, Research in Practice.

Announcing the first talk in a speaker series on Mathematics and Democracy!

The series will host a scholarly conversation on a broad range of issues where mathematics touches on matters of democracy: election theory, legislative redistricting, algorithmization of social infrastructure, access to mathematics, quantitative fairness, and the census, to name a few.

We are starting things off next week with CMU math professor Wesley Pegden, who was an expert witness in the Pennsylvania gerrymandering case. His team has proven a nice result in probability theory that adds further statistical rigor to an important new method for measuring gerrymanders. Here are the details:

Speaker: Wesley Pegden, Carnegie Mellon University Department of Mathematics
Location: NYU Center for Data Science, 60 Fifth Ave, Room 150
Time: 12pm, Tuesday May 8
Title: Detecting Gerrymandering with Mathematical Rigor

Abstract: In February of this year, the Pennsylvania Supreme Court found Pennsylvania’s Congressional districting to be an unconstitutional partisan gerrymander.  In this talk, I will discuss one of the pieces of evidence which the court used to reach this conclusion.  In particular, I will discuss a theorem which allows us to use randomness to detect gerrymandering of Congressional districtings in a statistically rigorous way.