Bayesian Statistics

Winter 2021, Winter 2022, Winter 2023

This course provides an introduction to Bayesian Statistics and its applications to data analysis in various fields. Topics include: (1) discrete models, (2) regression models, (3) hierarchical models, (4) model comparison, and (5) MCMC methods. The course combines theory with hands-on experience so that students can apply them to their own research.


Teaching Assistant for Dr. Antonio Rangel


There were three TA’s for this course, each handling a set of topics. The topics I was responsible for: (1) hierarchical models, (2) MCMC methods, and (3) model comparison.

  1. Held weekly office hours and managed 6-hour homework sessions twice a week for students to collaborate on problem sets and ask questions.
  2. Graded problem sets for approximately 90 students each week.
  3. Provided detailed feedback on in-class discussion problems for approximately 90 students each week.
Brenden Eum
Brenden Eum
PhD Candidate, Social & Decision Neuroscience