Bayesian Statistics

I only recommend this course to people who have sound knowledge in calculus and some background knowledge in Bayesian Statistics.

Very comprehensive course on Bayesian Statistics.

A good sampler of topics related to Bayesian Statistics.

I do hope that there will more MOOC's teaching Bayesian statistics soon.

The course is too sketchy: it does not provide enough materials to grasp the main ideas of Bayesian Statistics nor it gives any details about some formulas and important principles.This course does not have a book to follow along as the previous courses had (statistics).I had to spend more than 2 months to be able to understand all the concepts that this course was trying to teach.

This is one of many good courses that one can get a glimpse of Bayesian statistics though it lacks of thorough explanation of mathematical background and reading materials of any kind.

However, in the previous units I did not experience such issues It was nice learning all the distribution functions and Bayesian statistics.

I recommend Kruschke's "Doing Bayesian Data Analysis" as a very accessible way to learn Bayesian statistics.

A book or a reading material will help to better understand the concepts.I'm conscient that Bayesian statistics is more mathematics intensive, but you should find a way to make this course friendlier for beginner students in Bayesian statistics.

I'm not saying that each course should be accompanied by an e-book, but honestly, if I wanted to learn about Bayesian Statistics from Wikipedia I could have well skipped this class.The main reason I'm giving 2 stars to the course instead of 1 is the Labs and the Quizzes.

Even though they could use some polishing too, especially the final Lab, they are indeed very helpful and do a much better job at clarifying the concepts presented.All in all, I feel that if you want to learn about Bayesian Statistics you should look for another course, and/or save your money and get yourselves a good textbook.

And then there was Bayesian Statistics: much of the "instruction" in this course was truly awful.

The first three courses in this Duke series were superbly well done.

I appreciate very much what the Duke faculty achieved in the first three courses, but the treatment of Bayesian statistics that I have just suffered through was shameful.

There seems to be a significant disconnect between the first three courses (probability, inference, linear regression) and the fourth course (bayesian).

The first three courses in this specialization are very good, but somehow this course are way below the quality of the previous ones.

The first three courses were very good; you had the benefit of the free textbook that comes with them.

I have completed and reasonably understood the first three courses which were very interesting, well presented with basic concepts and implications continuously re-enforced.

I loved the first three courses immensely and they have re-enforced in me the desire to know and learn more about the topics and statistics in general.

Specially the first three courses given by Profr.

The first three courses are excellent but surprisingly this last course is a complete disappointment.

The last two weeks are way too hard to follow and could provide more practical examples instead of focusing on mathematical theory and formulas.

The lectures themselves can be hard to follow and often times skip over important calculations.

Really hard to follow and finish, especially compared to the other classes in this specialization.

The videos are hard to follow.

The specialists brought in were for some, a little bit hard to follow.

The lectures were hard to follow with fewer exercises to check your learning than in previous courses.

There is FAR too much here to be covered in a single module.

Week 3 was too much information too soon, but week 4 was great again like the other courses in this specialisation.

becomes too much confusing at times.

The pacing and structure of the course both felt off to me, spending too much time on some things (conjugacy in particular) and breezing past many other things too quickly (particularly numerical methods).

When material is beyond the scope of what perspective students can reasonably be expected to understand, faculty members should be honest enough to just say so rather than pretending to teach the subject matter.

I answered some of the quiz questions based on intuition and what looked reasonable rather than actually knowing how to solve them.

Even if the concept is understood the application part of it still remains a mystery on where to apply it, the course could have been more elaborate explaining these concepts in-depth rather than introducing without any prior background.

Its really hard for me to follow this specific course, its as if I am reading a summary of a novel rather than a novel, ideally this course should be broken into two courses and made into two five week courses.

I also thought that it would have been more helpful to learn to perform many of the analyses from scratch so that they could be better understood, rather than relying so heavily on the accompanying statsR package.

For sure the most challenging course so far.I'm amazed by how our statistical intuition fits with Bayesian approach and how we can get better results.I'm eager to use this concepts in new models at my job!

However, the course offered a glimpse on how Bayesian approach can deal certain issues where frequentist approaches fail and that is the most important lesson one can take home from this course.It would be very helpful if the teachers provide us an indication of a good book on Bayesian Statistic that is friendly to people that are not mathematically oriented (like myself).

Very different from the previous courses, this course uses the Bayesian approach to things already covered.

They just went way too fast through the material, even talking much faster.

They tried to put to much into this short course and consequently its way too hard.

I think that this course spend way too much time on theory (and breezing through it!)

In my opinion this is the most difficult course in this specialization.

The content should have been spread out over two courses in my opinion.

I really loved the previous courses because their reading material which was very good complimented by the video lectures, nevertheless, in this course, many of the video lectures was the repetition of the main book.