Really enjoyed the course! Thank you. I would have given a higher rating if: 1) the instructor had spend more time on the intuition underpinning different derivations, 2) provided more context, 3) discussed more examples from practice. However, I am definitely continuing on to "Bayesian Statistics: Techniques and Models"! Thank you once more, team UCSC!

I enjoyed the course. I was looking for a way to improve my knowledge of statistics and bayesian maths. I mainly used excel for the calculations. I would appreciate an additional tutorial on plotting mass and PDF function etc against Theta and real world variables to explore impact of parameters on distribution shape on prior and posterior results.

Exceptionally interesting class. Professor was knowledgeable and engaging. The key insight was to approach the "quizzes" as homework, a learning process. Some of the lectures were of variable audiovisual quality and the pacing of some sections was not uniform, but overall, a triumph. More from this professor please! Fun.

Herbert Lee is great at explaining the mathematics behind Bayesian statistics. However, I think the course can improve greatly by also focusing more on context and the intuition behind the mathematics. I often found that I was able to pass all quizzes, while I did not 100% understand why I was doing what I was doing.

Great discussion into the ideas. The quizzes are relevant to the lectures as well and pretty straightforward, you don't need to go outside of the lecture itself to be able to do the quizzes. the only thing would be it would be good if the lectures notes were in print as Prof. Lee's writing is sometimes hard to read.

As a grad student myself, I liked the way this course was presented in short video format and in only 4 weeks. Definitely there are much more to learn about Bayesian Statistics and one can go way deeper, but this course gives the required basic Bayesian knowledge to someone who wants to get familiar in a short time.

The course itself is well structured and covers a lot of material.

There are points in the course where the order of reading material and videos needs to be switched. Also, it would help to update some videos with a little more explanation. It appears as if the lecturer is skipping steps.

I liked it as introduction to Baysian statistics. With the material provided it was quite easily possible to answer the questions. I would have preferred that the videos of the course contained all the material and that it would not have been required to have read through material.

The course was well explained and there were several exercises pushing the learner to understand the logic behind the mathematical concept. I think it is a suitable class for people with already a certain level of statistics knowledge, even though all concepts are well explained.

I think that, besides lesson 11 and 12, everything was very well explained. I was a bit confused with lessons 11 and 12 since I am not new to econometrics. Perhaps I found it confusing the theory background related to the lessons themselves. Just my opinion, very good course.

The course was very well designed, I got to learn about a lot of new things in statistics that I had to understand. But for a Data Analyst working on large data sets and primarily working on ML this course is far too basic. Also, some of the concepts can be explained better.

I really liked the course.

What I think could be nice improvement would be more nsightful notes. Which means, that after every video, there should be a separate sheet with all the formulas being described in more detail, so that you can refer to them any time during quizes.

Overall the course is pretty good. They breakdown the concepts into clear and concise lectures. My only grip, is that the quizzes occur a little too frequently. They really interrupt the flow of the class. I would definitely prefer them spaced in 30-60 minute interval.

I found the need to search for most of the material needed to understand the lessons in other sources. Other than than it was a relatively easy class, which covers nearly the basics. This is not a tutorial on Data Analysis on R, although a short introduction is provided.

Course covers the concept in a very simple way. Examples and assignments are very good.

However some of the statements made throughout the lectures needs more explanation , the course did not dedicate any videos to get familiar with terminology related to probability.

It is a really interesting course. However, I think it should include more examples and meaningful ways to estimates some parameters. For example, how can I estimate alpha and beta for an Inverse-Gamma distribution in order to obtain a prior for the sigma-squared?

Pen hard to see against shirt. Was mildly irritating to wait for prof to write out stuff, maybe prewrite it?

Went too fast forward for me, would've liked complementary optional material, eg extra quizzes, to help understand and get used to the tougher parts.

Great introductions to Bayesian statistics and inference. Quiz is actually not easy just by passively viewing videos, so taking notes during lectures is strongly recommended. Do not be afraid the Honor quiz...they are not so different from the normal ones.

Likely course and practical: it help us to understand some basic notion for bayesian inference. But Some concepts are less clear and I think need more development and explication (like effective sample size, Jeffreys prior). Great job over all.

The lectures were good, but I hope more background materials can be released. Understanding the topics needs a relative solid mathematical background. Although having completed the course, I am still confused about some concepts in this course.

Really enjoyable.

My first free course, so this may be way off the mark in terms of norms, but I would have appreciated if supplementary material was either provided or suggested for doing more practice exercises, with worked through examples.

The course was excellent !...Giving a good overview of the basics needed to navigate through this topic. However, it would have been really great if some specific examples with respect to medicine and public health practice were incorporated

I found it to be a solid course. It has given me better grasp of the basics. I also found it a bit dry, and significant time spent on equations rather than high-level understanding. This is fine, as long as you know what you are in for!

Overall the class is great, especially the first two weeks' content is simple and well-explained. But from the week 3 to the week 4, the professor only writes many formula and doesn't provide enough examples to explain those formula.

Very high quality course. Could use some modifications (e.g. few more applied examples for regression using specific priors, MCMC etc.) and implementing some simple metaphors to introduce some topics before jumping into the maths.