Inference in context: Statistical theory and thinking | Jeffrey Bye

Abstract: The likelihood function plays a foundational role in statistical theory. I will demonstrate my teaching philosophy and approach through a lesson on maximum likelihood estimation and its connection to Neyman-Pearson, Bayesian, and other approaches to statistical and scientific inference. I will then expand on the role of context in statistical thinking, particularly how it informs my scholarship on how people learn about data, math, statistics, and programming.

Bio: Jeffrey K. Bye is an interdisciplinary teacher and researcher who received his Ph.D. from UCLA in Cognitive Psychology with a specialization in computational modeling and minor in quantitative methods. He has years of experience teaching undergraduate- and graduate-level statistics and programming at UCLA and University of Minnesota. His research blends cognitive and learning science approaches to understand how people learn and think about data, math, statistics, and programming. He is passionate about making science more collaborative, inclusive, and understandable to the public.