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.

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)

The first 3 weeks are excerlent scheduled. I took statistical inference course in university, but still confuse the content. But for week 4, whtn includes more advance material, this course just skip many detail.

The course provides a good explanation of a complex topic. I had trouble following some of the statistical mathematics but was able to understand the concepts and the different range of possible applications.

Short course that's actually mostly theoretical with a bit of R/Excel analysis. This fitted my needs perfectly. My only suggestion is that they should have released more comprehensive notes for the lectures.

The course content is great and provides a good introduction to bayesian statistics. The assignments could be a little more challenging as a lot of the questions require just plugging numbers into formulae.

I could grab the concept of Bayesian statistics but did not find the course fully self-contained. I had to look elsewhere to fully understand details. More complete supplementary material could help a lot.

Good use of R but maybe use the actual coefficient from the equations themselves rather than picking numbers pre-selected which may confuse.

Unable to look at discussion forum without posting myself.

This is a good course for reviewing basic concepts of statistics, and good for starting learning Bayesian, as introduced as a basic course. If you want to learn deeper, go and find another course!

the notes for the lectures are missing.

In my opinion the notes, which includes the video materials could be very useful.

the course was good. I learnt some new concepts in bayesian thinking.

Good course. As a recommendation to improve it, it would have been very helpful if the lectures (PDF) given with each lesson included all the formulas and explanations given in the videos.

Very clear and informative. Would like a more extensive and combined reference material (PDF, so less need to lookup e.g. definitions of effective sample size for various distributions).

It was a good course for me to get familiar with the new perspective on statistics. Thank you!

Maybe, some extended practice exercise at the end of the course would make it even better)