by Sarah Brauner (University of Pennsylvania), Zajj Daugherty (Reed College), Sarah Mason (Wake Forest University), and Anne Schilling (University of California, Davis)
A common story in mathematics is the following: you have a large set of data, and want to find a strategic way to group that data together that makes it simpler to understand. The challenge here is to find a good way to group things that actually distills the information you have, and removes some of the “noise” of the full data set. For example, if your data set measures income by address in a city, it might make sense to group data points by neighborhood, but grouping neighborhoods this way might oversimplify the situation.
