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.
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 Kuntal B•
Thanks, Coursera. This is a good course. It would be helpful if we get any proper class notes on Jeffrey's prior and Multivariate regression.
par Artem B•
Great course with a lot of simple, but illustrative exercises. It may be useful to have some basic prior knowledge of econometrics/statistics
par Michael W•
Great introductory course. It was challenging but doable for someone who has not take college level mathematics or statistics in a few years.
par Robert K M•
Invaluable. Excellent quizzes. A few terms could have been better defined, and a few more examples wouldn't hurt, but overall excellent.
par Damian C•
Very well presented course. Interesting and intuitive introduction into the fascinating Bayesian world.
Many thanks and congratulations!!!
par Howard H•
Excellent introduction to Bayesian statistics -- lectures, readings, and quizzes provide excellent support to learning the main concepts.
par Ariel A•
Great course, it has the right proportion of theory and practice. It's a great start for anyone who wants to dive into Bayesian Analysis.
par Hari S•
Thought is a simple manner. Made complex concepts look very easy. Would surely recommend this course. Thanks Prof. Herbert Lee and team.
par Vignesh R•
Awesome course that helped me overcome the Bayesian statistics way of thinking hurdle. Now, I want to go on and learn MCMC, Metropolis !
par Qinyu X•
The course is generally great. Nonetheless, it is not recommended for those without a statistical background and knowledge of calculus.
par Naseera M•
Very good course. Prof. Lee explains each concept well. Bayesian Stats makes more sense to me now than before!!
Thanks so much Prof. Lee
par Gustavo C•
I loved this course, I learned a lot and I hope I will be able to use this knowledge when I go back to college for my Master's degree.
par Evgenii L•
A very good course. Even better if you continue with the 2nd course that teaches about how to implement Bayesian data analysis in JAGS
par Joseph G•
I enjoyed the lecturer, the material is relevant, and the tests are well tailored to ensure you are absorbing the correct information.
par Rodrigo G•
Give you great insight. Very intuitive. Although we went through the last week rather quick (more explanation would have been better)
par Jenna K•
The lectures are at the right pace; concise and challenging. Great examples. Thank you so much for providing us with great materials.
par Matthew S•
Pretty challenging course. Well organized and well delivered. I learned from the exercises and also the feedback from the exercises.
par Dr. R M•
Very informative and clear presentation of the material, which makes it fun and quick to learn the topics. Very good quiz questions.
par Xiaoyang G•
This course is a very good introductory of bayesian statistics. But it better that you have known the basic statistics inference.
par Humberto R C•
A clear and compact introduction. Quizzes and exercises are relevant. I got acces to grades and feedback in the audit one I took.
par Raj s•
Learned something new :). Lecture were excellent, but, I need time to digest and hope I will get opportunity to use it in future.
par Tetsuhiko O•
I studied basic theory from these lectures. I will try again and again until I understand Baysian Statistics concept completely.
par Felipe C•
Quite interesting course ant not too long. I learnt many interesting and useful concepts in statistics. Highly recommendable.
par Jose M R F•
Very well explained. Lectures are given in a very nice way as the professor writes. Exercises and quizzes are very well done.
par Zhirui W•
Become very clear about all the formula and derivation of Bayesian Statistics after taking this course. Strongly recommended.