Back to Bayesian Statistics

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763 ratings

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247 reviews

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."...

RR

Sep 20, 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.

GH

Apr 9, 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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By 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.

By Artur A B

•Sep 2, 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.

By Tiago M d R F

•Jun 16, 2020

I'm not at all confortable with bayesian statistic after completion of course with very good grade. I think course lacks a step by step explanation of some core concepts. Or maybe it should have less concepts. I ended up searching for help outside (youtube, etc).

By 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.

By Ashley J

•Jun 19, 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.

By 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.

By Pedro 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.

By 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.

By Marcus V C A

•Jul 6, 2020

I think the content is very good, as well as the online book and the supplementary material. But the videos for Weeks 3 and 4 could be better ... In my opinion, they should be longer and more explanatory.

By Amy W

•Apr 19, 2020

Until the last two weeks, this course was very good. The lectures in the last couple of weeks contained lots of information and not very many examples. The third week, especially, was overwhelming.

By 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.

By 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.

By Luv S

•May 3, 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.

By Jennifer g e

•Apr 10, 2021

I learned a lot but i think the teachers should explain with more examples, the things they explain seem very abstract and i had to look for extra help.

By Santiago S

•Jul 14, 2018

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

By Tasmeem J M

•Aug 6, 2020

This course gave me a hard time. The lectures from week 3 and 4 seemed difficult, some more resources would be helpful.

By Stephanie A

•Mar 18, 2020

Like in all courses of this specialization, the peer assignment was a real bottle-neck in the completion of the course.

By Pauline Z

•Aug 22, 2020

This is certainly a good introduction. But it did not help me to be independent on bayesian statistics

By dumessi

•Sep 7, 2019

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

By Rob M

•Sep 27, 2017

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

By Stefan H

•Mar 16, 2019

Find it hard to follow the lectures. The labs and supplement material is good though.

By Kalle K

•Jun 16, 2020

A useful course, but very demanding. Many of the lectures are fast-paced.

By Gustavo S B

•Sep 17, 2017

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

By Li Z

•Aug 15, 2019

Some contents are just too difficult to understand fully.

By Christopher C

•Feb 12, 2018

Very heavy information very quickly otherwise - great

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