Data Science ARES: Alicia Johnson

Dr. Alicia Johnson
Associate Professor of Statistics
Department of Mathematics, Statistics, and Computer Science,
Macalester College

Free Event | Registration Required

Talk Title: Demystifying Bayesian statistics

Abstract: In a survey of high-ranking institutions, only 6 of 50 colleges and 45 of 102 universities offer an undergraduate course in Bayesian statistics (Dogucu and Hu, 2021). Given the rising popularity of Bayesian statistics, this absence from the common curriculum likely reflects an assumption that the topic can’t be taught at the undergraduate level, not that the topic isn’t important to undergraduate learners and comparably trained practitioners. In this talk, I’ll discuss our strategies to push back on this assumption in Bayes Rules! An Introduction to Applied Bayesian Modeling (Johnson, Ott, & Dogucu, 2022). Beyond a careful consideration of mathematical level, these strategies reflect our belief in the importance of inclusive, ethical, and active learning pedagogy and the importance of being human.

Speaker Profile: 

Alicia Johnson is an associate professor of statistics at Macalester College, a liberal arts institution in St Paul, Minnesota. Her research interests span Bayesian statistics, computational statistics, and statistics / data science education. Along with Miles Ott and Mine Dogucu, she co-authored the book “Bayes Rules! An Introduction to Applied Bayesian Modeling” (2022), and is a strong believer that the (Bayesian) statistics community can be broadened through more accessible and inclusive pedagogy. Outside of statistics, Dr. Johnson enjoys building things, four seasons, and any activity that involves fresh air (among other things).


The event is finished.

Local Time

  • Timezone: America/New_York
  • Date: Mar 07 2022
  • Time: 3:30 pm - 4:30 pm

Location

Zoom
Online

Labels

DS & Statistics

Organizer

Esther Berzunza
Phone
416-689-7271
Email
esther.berzunza@utoronto.ca