This is a good course if you know probability and want to practices

Excellent course, but the lack of the written notes is a big minus

Satisfied with the course in general. Good investment of my time!!

Quite harsh but give me some insight on prediction and estimation

It would have been better to have more data analysis applications

These are a lot of stuffs that the professor didn't say clearly.

Good introductory course. Could provide more hands-on examples

For me Chinese, it 's not easy to understand the quiz.

Clear and consise introduction to Bayesian statistics

Good and simple introduction for Bayesian statistics.

well instructed basic course of Bayesian statistics.

More examples are required as well as more practice

Loved the theory & analytical part of the course.

It is a nice introductory course on Baysian s

Pretty good overview of Bayesian statistics.

from week 3, the learning curve become steep

The normal distribution part lacks detail.

Good overview of Bayesian statistics.

Nice and easy introduction course.

Liked it and can recommend it.

A good course - recommended.

Need more material on R.

Very good introduction!

I am working in the field of epidemiological, medical research. Overall I would recommend taking this course. It needs to be pointed out, however, that if you are outside of the field of mathematics this specific course entails a lot of research (using google etc) that needs to be undertaken to understand the course material. Maybe in the future the course directors can compile a summary of all important formulae etc so that professionals from sectors other than mathematics can follow more easily and can focus much on this particular course on Bayesian statistics and not so much on conducting additional research to understand the basic course material. Furthermore, alongside a summary formula sheet it would be good to have all explanations included, what the parameters (alpha, beta etc) stand for with regards to the specific context. Thank you very much for this course!

This course provides a good overview to Bayesian statistics, but a larger dose of explanations of would be very useful. Mr Lee discusses, in the beginning, the differences between frequentist and bayesian paradigm. I feel that this would be beneficial in the other parts of the course, too. I feel that many of the lectures simply go too fast. After lectures full of Math, it would be useful to present lectures analyzing what had just been taught, in order to better grasp the content. And in general, this happens through the whole course - most lectures are basically math, without much time for grasping the intuition and underlying logic. For example: in the final part, under linear regression, it might be be difficult to grasp what a bayesian predictive interval means. All in all, I recommend this MOOC, but you might find hard to fully grasp it.