You are here
- Home >
- Data Science in 30 Minutes: Establishing a Standard for Partisan Gerrymande...
Data Science in 30 Minutes: Establishing a Standard for Partisan Gerrymande...
Can Math Help Repair Our Democracy? Using Simple Statistics to Establish a Standard for Partisan Gerrymandering
In representative democracy, a winner-take-all system has a bug, in which legislators can choose their voters, instead of the other way around. This leads to noncompetitive races and distorted outcomes, for instance the
ability of a minority of voters to elect a majority of representatives. This phenomenon is known as partisan gerrymandering. Can math help repair this situation? In this talk, Sam will show simple statistical tools that, if accepted by the U.S. Supreme Court, will repair a flaw in how we elect our government and help make legislatures more responsive to the will of voters.
Sam Wang, PhD is professor of molecular biology and neuroscience at Princeton University. His work focuses on the neurobiology of learning, at levels ranging from single synapses to the whole brain.
Michael Li founded The Data Incubator, a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants.