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3.9

566 Bewertungen

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169 Bewertungen

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.

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von 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.

von 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.

von Robert M M

•Sep 27, 2017

Slides poor compared to 3 earlier modules and instructor not as engaging. However, the labs are good.

von 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.

von 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.

von Xinyi L

•Aug 15, 2017

not very interested

von 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.

von Vivian Y Q

•Oct 13, 2017

huge jump

von 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.

von 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.

von 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.

von 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......

von Gustavo S B

•Sep 17, 2017

I would recommend to include more weeks; slow down and go deeper

von 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.

von Christopher C

•Feb 12, 2018

Very heavy information very quickly otherwise - great

von 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.

von 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.

von 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.

von 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.

von 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.

von Li Z

•Aug 15, 2019

Some contents are just too difficult to understand fully.

von Wei C C

•Dec 06, 2018

The materials and response from the organization are unavailable for a while and never get an answer

von Witold W

•Sep 26, 2017

Tons of interesting material. However, presented in a way which is hard to take, and harder to remember, especially if you are used to the exceptionally high standards of Coursera. The slides, which I am used to work with, are a big let down. They are hard to follow, erratic, lack thoroughness and are incomplete. It does not make it better that they refer you all the time to additional material. Also the lectures are disappointing. The lecturers do not interact with the slides, they don't explain. I wished I could have taken more from the course since I think that the topic is relevant and interesting. Really disappointed. I do hope that there will more MOOC's teaching Bayesian statistics soon.

von Adara

•Dec 04, 2017

The course presents interesting material but it is not easy to follow. It is a huge jump from the previous courses and requires far more hours to understand all the (math-heavy) material than the stated. The slides feel a bit chaotic and the language/sentences during the explanations could be much simpler. At times it feels that the instructors limit themselves to reading formulas one after another, making it hard to find a connection between them and how they are applied.

von Minas-Marios V

•Apr 26, 2017

Honestly, I find it very hard to recommend this course to anyone. First of all, let's note that the course covers quite more advanced topics than the previous 3 courses in the specialization, so some extra difficulty is to be expected. However, the main problem I encountered was with the video lectures themselves, particularly during the 3rd and 4th week of the course. The instructor does a very rushed job at explaining everything, constantly giving us tons of information and jargon that is not previously mentioned, and even the examples fail to give us insight at what we need to do and why.

Other than the lectures, no external material is given to help us decipher what the professors are saying, other than a few Wikipedia links. 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.

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