I am working on innovative approaches to introducing Bayesian statistics in the undergraduate statistics curriculum.
GRANTS
National Science Foundation (NSF)
Project title: Advancing Bayesian Thinking in STEM.
Role: Principal Investigator (PIs: Dogucu (UC Irvine) and Herring (Duke University)).
Period: Dec. 2022 – Nov. 2025.
Amount: $300,000.00
Liberal Arts Collaborative for Digital Innovation (LACOL)
Project title: Bayesian Statistics.
Role: Principal Investigator.
Period: Oct. 2018 – June 2022.
Amount: $27,500.00
Liberal Arts Collaborative for Digital Innovation (LACOL)
Project title: Bayesian Inference with Python.
Role: Principal Investigator.
Period: Jan. 2020 – June 2020.
Amount: $3,000.00
BOOK PROJECTS
Albert, J. and Hu, J. (2019), “Probability and Bayesian Modeling”, Texts in Statistical Science, Chapman & Hall CRC Press. Text website
TEACHING AND LEARNING MATERIALS
A GitHub repo on Vassar’s Bayesian Statistics course material (lectures, labs, homework, cases studies etc.)
I maintain a GitHub repo on various resources for undergraduate Bayesian education – let me know if you have recommended material to be added to the repo!
SHORT COURSES AND WORKSHOPS
“Bayes BATS”, an NSF-funded bootcamp for STEM educators to introduce Bayesian methods in their curriculum (co-presenter), July 2023 (link)
“Bayesian Thinking: Fundamentals, Computation, and Hierarchical Modeling”, ISI short course (co-presenter), January 2023
“Introducing Bayesian Statistical Analysis into Your Teaching”, eCOTS 2022 pre-conference workshop (co-presenter), May 2022 (link)
“Introducing Bayesian Statistical Analysis into Your Teaching”, USCOTS 2021 pre-conference workshop (co-presenter), June 2021 (link)
“Bayesian Thinking: Fundamentals, Computation, and Hierarchical Modeling”, JSM workshop (co-presenter), November 2020 (link)
“Introduction to Bayesian Inference in R”, Bureau of Labor Statistics short course, Washington D.C., October 2018
PRESENTATIONS AND PANEL DISCUSSIONS
“Examples from Two Undergraduate Bayesian Courses”, Symposium on Data Science & Statistics (co-presenter), June 2021 (link)
“Bayesian Methods and the Statistics and Data Science Curriculum”, CAUSE & JSDSE webinar series (panelist), February 2021 (slides and recordings)
“Using CE Microdata in Undergraduate Statistics Courses”, 2019 Consumer Expenditure Surveys (CE) Microdata Users’ Workshop, Washington D.C., July 2019 (slide deck)
“Teaching an Undergraduate Bayesian Statistics Course”, Statistical Science Department Seminar, Duke University, NC, December 2017
SERVICE
Organizer and Discussant, “Introducing Bayesian Methods in Statistics and Data Science Curriculum” (topic-contributed), JSM 2023
Section Chair, Education Research and Practice Section, International Society for Bayesian Analysis (ISBA), 2023 – 2025
Organizer, “Recent developments in Bayesian education” (invited), ISBA 2022
Breakout Room Lead, “Teaching Bayesian Statistics”, Prepare to Teach 2021 (slide deck)
Organizer & Chair, “Thinking beyond the p-value: advancing Bayesian education for the undergraduates” (invited), Joint Statistical Meetings 2020 (summary)
Treasurer, Education Research and Practice Section, International Society for Bayesian Analysis (ISBA), 2017 – 2019
Organizer & Discussant, “Introducing Bayesian Statistics at Courses of Various Levels” (topic-contributed), Joint Statistical Meetings 2017
PEER REVIEWED PUBLICATIONS
Kejzlar, V. and Hu, J. (2024), Introducing variational inference in statistics and data science curriculum, The American Statistician, 78(2), 359-367.
Hu, J. and Dogucu, M. (2022), Content and computing outline of two undergraduate Bayesian courses: tools, examples, and recommendations, Stat SDSS 2021 Special Issue, 11(1), e452. Open Access
Dogucu, M. and Hu, J. (2022), The current state of undergraduate Bayesian education and recommendations for the future, The American Statistician, 76(4), 405-413. Open Access
Albert, J. and Hu, J. (2020), Bayesian computing in the undergraduate statistics curriculum, Journal of Statistics Education, 28(3), 236-247. Open Access
Johnson, A., Rundel, C., Hu, J., Ross, K. and Rossman, A. (2020), Teaching an undergraduate course in Bayesian statistics: a panel discussion, Journal of Statistics Education, 28(3), 251-261. Open Access
Hu, J. (2020), A Bayesian statistics course for undergraduates: Bayesian thinking, computing, and research, Journal of Statistics Education, 28(3), 229-235. Open Access
WORK IN PROGRESS
Dogucu, M., Hu, J. and Herring, A., Statisticians training STEM educators in statistics methods and pedagogy: a case study of instructor training in Bayesian methods, under revision.