This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution. Additionally, the course will introduce credible regions, Bayesian comparisons of means and proportions, Bayesian regression and inference using multiple models, and discussion of Bayesian prediction.
We assume learners in this course have background knowledge equivalent to what is covered in the earlier three courses in this specialization: "Introduction to Probability and Data," "Inferential Statistics," and "Linear Regression and Modeling."...

Sep 21, 2017

Great course. Difficult to apprehend sometimes as the Frequentist paradigm is learned first but once you get it, it is really amazing to see the believe update in action with data.

Apr 10, 2018

I like this course a lot. Explanations are clear and much of the (unnecessarily heavyweight) maths is glossed over. I particularly liked the sections on Bayesian model selection.

필터링 기준:

교육 기관: 陈昊

•Nov 15, 2017

Harder than former courses but great!

교육 기관: George G R

•May 06, 2017

The classes are good.

교육 기관: sohini m

•Oct 27, 2017

It was nice

교육 기관: Haixu L

•Jan 19, 2018

The material is interesting. However some of the points are not presented in a way that I can understand.

The course is less coherent than the previous ones.

This course gave me an impression that the materials are not well organized. Basically, the course organizers present a lot of concepts and materials to you without background introductions. I know there are a lot to cover in 5 weeks. The organizers should think this through about how to present a lot of information in a short period of time. Maybe put the less important information in a lecture notes or something could be better.

교육 기관: Jeff M

•May 09, 2019

Overall I think there are better options available for learning bayesian statistics. 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). 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.

교육 기관: schlies

•May 31, 2019

It seems like this course contains good information, but there's a huge gap in the material as taught by some of the instructors. It seems like one of the instructors in particular assumes you're already familiar with material that's not covered in the rest of the course. These parts of the lectures rehearse math and code in a very formulaic way which conveys almost no intuition or understanding of the subject matter. However, the labs a pretty good.

교육 기관: Bo L

•Dec 08, 2017

This course is different from the first 3 courses in this specialization. I only recommend this course to people who have sound knowledge in calculus and some background knowledge in Bayesian Statistics. Personally, the pace of the videos is fast and the instructors use very technical terms. Although the course is not intended to give in-depth explanation into Baysian statistics, how the content is set up tend to be confusing.

교육 기관: Thomas J H

•Aug 07, 2017

This course has a much steeper learning curve than the first three, and goes from theory to examples in action rather than vice versa. I think the Professors involved are super-smart and more than just qualified, but the teaching method is a noted departure from the first three courses in this series. Think this would work better as two courses. Slow things down a bit, and give more R exercises and examples.

교육 기관: Andreas Z

•Mar 27, 2018

This introduction to Bayesian statistics familiarises you with the fundamental concepts. The difficulty is that the material covered is non-trivial and probably cannot be squeezed into the time allocated. Is is very difficult to follow the lectures and not getting lost. Thus, you need to take lot of time and maybe complement this course additional ones in order to understand the material and profit from it.

교육 기관: Etienne T

•Nov 20, 2017

This course delved too deep in the math that were not always explained as good as the other courses in this specialization. Really liked the prof from the other courses (Mine), she really explained well... Didn't like the teaching style of the prof in this course unfortunately. Didn't have a good reference book that we could refer to like the other courses. This was really a pain.

교육 기관: Erik B

•Feb 26, 2017

After 3 great courses in this specialization, this one was disappointing. The content just isn't explained well in the videos. The Labs were fine. I'm sorry but the course seemed rushed, and it isn't great marketing for the Bayesian approach. As a consequence, I am now not sure if I want to do the capstone......

교육 기관: Elvis S R

•Sep 10, 2019

I don't think the level of this course is in continuity with the previous three of the specialization. The first average of the classes are as usual, but then the topics become harder and equation-oriented. Less examples are developed and I wasn't able to learn everything as it happened in the previous courses.

교육 기관: Dgo D

•May 22, 2017

I consider that you need to change the scope of this last course. 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.

교육 기관: Tony M

•Oct 23, 2016

I found some of the instructional videos a bit confusing. It was difficult to understand the underlying methodology of some of the concepts explained. I believe the instructors assumed the students had a more rigorous understanding of the underlying calculus than was suggested for this course.

교육 기관: Artur A B

•Sep 02, 2017

This course might better serve the students by having more intuitive examples shared before the quiz/programming exercises. I think the topic deserves more attention (2 weeks instead of 1) or perhaps offered as part of a series of bayesian courses in a different certification.

교육 기관: Charlotte C

•Feb 15, 2020

Very different from the previous courses, this course uses the Bayesian approach to things already covered. The specialists brought in were for some, a little bit hard to follow. More activity on the forum from the organisers would also be much appreciated.

교육 기관: Ashley J

•Jun 20, 2017

Good breadth of useful information and well intentioned lectures, but this course really needs a companion text and practice questions outside of the quizzes to reach the level of effectiveness of the other courses in the specialization.

교육 기관: Guillermo U O G

•May 12, 2019

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.

교육 기관: Pedro M E

•Mar 15, 2018

Course is much harder to follow than previous courses. Due to change of instructors, the notation used wasn't always introduced before and is not explained. Feels rushed if you hadn't previous notions of the subject.

교육 기관: Sophie G

•Jul 25, 2018

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

The concepts might be more complex, but the way they're taught also adds to the difficulty, in my opinion.

교육 기관: Shaurya J S

•Mar 20, 2018

Not as good as other courses in this specialization. Most of the times the focus was to teach the method of performing a Bayesian Statistical process rather than teaching the actual concept.

교육 기관: Ganesh H

•Aug 17, 2017

I felt the course ramps up from the basics way too quickly. I didn't like the pacing in the course compared to other courses in the same specialization, although I did learn a lot.

교육 기관: Luv S

•May 03, 2018

Explanations not simplified as compared to the other courses in the specialisation. Very difficult to comprehend. Instructor should take more time to explain the fundamentals.

교육 기관: Santiago S

•Jul 15, 2018

Se trata de explicar términos matemáticamente complejos de una manera muy general y vaga dificultando el entendimiento y el aprendizaje del tema.

교육 기관: dumessi

•Sep 08, 2019

The explaining for some bayesian methods are unclear, which make it harder for new learner to follow.