Very concise and informative introduction to Bayesian statistics. Requires a fair bit of research besides just watching the course videos. But that only adds to the fun. Feel much more confident in my ability to estimate uncertainties in model parameters / predictions now.

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.

The course design is fine structured. However , little explanation on the concepts presented in the course, more examples or clarification needed on utilizng the formulas and the underlying ideas. The quizzes in video was much helpful for the learning .

Honestly wish there were more practice problems that I could do outside of the quizzes. Just make them optional. It's just tough to iterate on the same problems and work to figure them out. Otherwise I really enjoyed the course and found it really helpful.

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.

For me at least, it became hard to follow around module 3. The linear regression part seemed like a step backwards, as we had been touting the benefits of the Bayesian perspective, only to end up with the same results as the Frequentist perspective.

the course forms a very good basis for those who want to learn the mathematics behind Bayesian statistics and it had been a lot of fun. A lot of concepts that had been vague were clarified to me during this course appreciate all effort by Prof. Lee.

Overall, the course is very informative and lively, helped me get in touch with the wonder of fundamental Bayesian Statistics. However, some courses in the later chapters are taught somewhat simple, so that I spent a lot of time finding reference.

Globally a good course, although it is a bit rushed towards the end on the part that concerns Bayesian linear regression. I would probably add a fifth week to explain that in more detail, relying less on software and more on developing the maths.

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.

The Course was concise and helpful to build a foundation for Bayesian statistics. However, it is not recommended for those who has weak or no background in statistics, as the explanation are not thoroughly explained by details.

Well instructed course for a person who has a good understanding of probability theory. I had to take some time and revise the concept as in the beginning I struggled to understand probability distributions. The rest was good!

The course is quite difficult to comprehend with a loose background on stats, but the lessons prove to be interesting especially when applied to sample experiments. Eager to try the next course on Bayesian Statistics.

Very good course for beginning bayesian inference. The syllabus is easy to follow, but I also think one could benefit even more by complementing the lectures with other sources (books or other youtube explanation)