Distinguished Lecture Series
Paul Gustafson
Department of Statistics at the University of British Columbia
Room: DC 1302
Bayesian Inference when Parameter Identification is Lacking: A Narrative Arc across Applications, Methods, and Theory
Despite several proposed roadmaps to increase diversity in scientific research, most of the world's research data are collected on people of European ancestry. We rely on summary statistics from historically privileged populations and then devise clever statistical methods to transfer/transport them for cross-ancestry use. In this talk, I would first argue the obvious: for building fair algorithms we need fair training datasets. However, till we have reached the dream of equitable big data at a global scale, statisticians have an important role to play. In fact we have the perfect tools to study the "unobserved" through modeling of missing data, selection bias and alike. I will share examples from my personal journey as a statistician where doing good and timely statistical work with imperfect data quantified important disparity in health outcomes and led to policy impact. I will conclude the talk with a call to arms for statisticians to lead efforts for creating, curating, collecting data and pioneering new scientific studies, not just remain on the design and analytic fringes. As public health statisticians, our job is not just to predict, but to prevent. The talk is based on years of work with my students and colleagues at the Department of Biostatistics, University of Michigan and inspired by the transformative experience we shared as a statistical team working on the COVID-19 pandemic.
Paul Gustafson
Paul Gustafson is a Professor in the Department of Statistics at the University of British Columbia, Vancouver. He is a Fellow of the American Statistical Association, the 2008 recipient of the CRM-SSC Prize in Statistics, and the 2020 Gold Medallist of the Statistical Society of Canada. His research interests include Bayesian methods, causal inference, evidence synthesis, measurement error, and partial identification. He has authored two books: Measurement Error and Misclassification in Statistics and Epidemiology: Impact and Bayesian Adjustments (2004, Chapman and Hall / CRC Press), and Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data (2015, Chapman and Hall / CRC Press). He was the Editor-in-Chief of the Canadian Journal of Statistics (2007-2009), and is currently the Special Editor for Statistical Methods for the journal Epidemiology. At UBC, Paul served as a founding Co-director of the Master of Data Science program, and he will soon embark upon a second term as Head of the Department of Statistics.
David A. Sprott (1930-2013)
Professor David Sprott was the first Chair (1967-1975) of the Department of Statistics and Actuarial Science at the University of Waterloo and first Dean of the Faculty of Mathematics (1967-1972). The David Sprott Distinguished Lecture Series was created in recognition of his tremendous leadership at a formative time of our department, as well as his highly influential research in statistical science.