Bayesian statistics is becoming more common in scientific practice and workforce. Thus, the inclusion of Bayesian training in statistics and data science curricula at the undergraduate level is more important than it has ever been. With the advances in computing power and modern educational tools, undergraduate Bayesian education is evolving. In this talk, we will cover the current state of Bayesian education at the undergraduate level. We will discuss different approaches and discover common themes in terms of content, software, and assessment in Bayesian classes.
Mine Dogucu is Assistant Professor of Teaching and Vice Chair of Undergraduate Studies in the Department of Statistics at University of California Irvine. Her goal is to create educational resources for statistics and data science that are accessible physically and cognitively. Her work focuses on modern pedagogical approaches in the statistics curriculum, making data science education accessible, and undergraduate Bayesian education. She is the co-author of the book Bayes Rules! An Introduction to Applied Bayesian Modeling. She works on a few projects funded by the National Science Foundation and the National Institutes of Health. She writes blog posts about data, pedagogy, and data pedagogy at DataPedagogy.com.