学生对 加州大学圣克鲁兹分校 提供的 Bayesian Statistics: Techniques and Models 的评价和反馈

It is very concise, but informative course. It combines both theory and practice in R, which are easy to follow.

Very nice course. A bit more theory on sampling methods would be welcome.

Complex subject made easy with easy to understand theory & practical examples

Very good course, a little bit to slow at some point but this is marginal in the overall feeling.

Thank you!

Perfect combination of theory part + application part

Recommend to people who took the basic Bayesian class

Good balance between courses and codes exercises

really like the content.

the R material in this actually changes my view towards R, so thanks.

I thoroughly enjoyed participating in this course, and I do think that I learned a fair number of skills of real conceptual and practical value. Thanks to the instructors' team for their dedicated efforts.

Really good intermediate introduction to bayesian analysis. I really liked how hands-on the course is. The last project was very useful as one will likely to face challenges and try to solve them especially if you use a rich dataset.

The course provided a lot of very helpful tools. However, I believe it was a bit too fast paced. Furthermore, there were certain topics which were not explained clearly -- for example, the discussion of the Metropolis-Hastings Algorithm and Gibbs Sampling was extremely confusing.

Informative but the pace is slow

Good course, but the peer review process for the Capstone project in Week 5 is broken. Based on submissions to the course Forum in which multiple students have submitted their work on time but not received a grade due to lack of peer reviewers, this has been going on .

This course is taught in a way that not useful for real world applications.

Not enough depth.