Statistics for a Computational Topologist, Part I

Tuesday, August 14, 2018 - 4:00pm - 5:00pm
Lind 305
Brittany Terese Fasy (Montana State University)
To solve real-world data analysis questions, researchers from different fields must collaborate. Topological data analysis (TDA) combines algebraic topology (mathematics) and algorithmic developments (computer science). Recent developments in the field introduce statistical concepts to TDA.

In Part I, we will discuss general questions we face in data analysis and explore the (one-dimensional) persistence diagram as a data descriptor. In particular, we will explore a statistical tool called bootstrapping in order to computer confidence sets for persistence diagrams.