SDS 4310
Bayesian Statistics
Introduces the Bayesian approach to statistical inference for data analysis in a variety of applications. Topics include: comparison of Bayesian and frequentist methods, Bayesian model specification, choice of priors, computational methods such as rejection sampling, and stochastic simulation (Markov chain Monte Carlo), empirical Bayes method, hands-on Bayesian data analysis using appropriate software.
Instructors
Reviews
0 exposure and nothing to learn; after few weeks you will find out 80% students will not come to class since it's just a waste of time.
4/22/2023
I definitely liked Kuffner, but I also understand the negative reviews. His lectures are a bit dry, and he does just read off of on his slides. However, I still felt like the slides were well-prepared and organized. He moves quickly and covers a ton of content, but he's also good at answering questions or meeting outside of class to clarify things.
5/10/2022