Statistics When n Equals 1


Benjamin Recht
Department EECS, University of California, Berkeley


Marzyeh Ghassemi
Abstract: 21st-century medicine embraces a statistical view of effectiveness. This view considers the implications of treatments and diseases as best understood on populations. But such population conclusions tell us little about what to do with any particular person. This talk will first describe some of the shortsightedness of population statistics when it comes to individual decision-making. As an alternative, I will outline how we might design treatments and interventions to help individuals directly. I will present a series of parallel projects that link ideas from optimization, control, and experiment design to create statistics and inform decisions for the individual. Though most recent work has focused on precision, focusing on smaller statistical populations, I will explain why optimization might better guide personalization.

Bio: Benjamin Recht is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research has focused on applying mathematical optimization and statistics to problems in data analysis and machine learning. He is currently studying histories, methods, and theories of scientific validity and experimental design.