31 août 2017
Good intro to Bayesian Statistics. Covers the basic concepts. Workload is reasonable and quizzes/exercises are helpful. Could include more exercises and additional backgroung/future reading materials.
16 oct. 2020
An excellent course with some good hands on exercises in both R and excel. Not for the faint of heart mathematically speaking, assumes a competent understanding of statistics and probability going in
par Jerry S•
13 mars 2017
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.
par Brian M•
21 mai 2020
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.
par Akshay N•
4 sept. 2017
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
par Jakob W•
15 mars 2018
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!
7 janv. 2020
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.
par P G•
17 juin 2019
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.
par Masoud A M•
16 août 2020
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.
par Curt J B•
20 nov. 2020
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.
par Yahia E•
4 mai 2019
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)
par Ran L•
12 août 2021
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.
par Paul B•
19 août 2020
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.
par Bojan B•
9 avr. 2017
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.
par Raja G•
11 déc. 2019
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.
par Leszek B•
15 janv. 2018
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.
par Marc S•
10 oct. 2018
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.
par JIONG L•
21 avr. 2021
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!
par Michael D•
19 févr. 2020
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.
par Enrique D T•
23 juin 2020
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.
par Michael M•
25 sept. 2019
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).
par Danil G•
9 déc. 2019
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)
26 nov. 2016
A good course but neither notes nor lectures were not in much details. But still it was worth my time. I strongly recommend it if you want a subtle introduction to Bayesian Statistics.
par Satish C S•
28 août 2021
This course is vary helpful for the understanding of the basics of Bayesian analysis. The course material are fantastic as well as the teacher. Good introductory Course in My opinion.
par Steven S•
7 juil. 2017
Great course (and teacher). Assumes some basic highschool level for math. With experience in frequentist statistics, but not all the distributions this course was "easy" to follow.
par Antonio H•
20 févr. 2021
Great course in a difficult subject. Well structured. Requires some previous knowledge otherwise difficult to follow. Big thanks to professor Lee for bringing to us this content.
par Óscar S F•
19 sept. 2017
Very straight-to-the-point course. Very dense, though, for a newbe in bayesian terms and concepts. But I definitely suggest it to undertand priors and posterior concepts. Thanks!