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.

筛选依据：

创建者 Aydar A

•Dec 20, 2017

The worst course in the series.

It progresses at a hurricane speed, thus as usefull as the Maria. I have barely made and it was not a pleasant experience. In fact I drowned at the week 4. The only reason I did not drop the course is because I've already paid for the previous courses of the specialization and I need to complete specialization for the certificate.

I think only people who had bayesian stats before and take this course as a refresher might find it pleasant. Or people with very good knowledge of probability theory. For others it is just a waste of time, because you will not learn to sail during a hurricane.

I have checked the syllabus of the other course on Bayesian Stats offered on coursera and it covers the same material in 8 weeks(2 courses), so that course would probably be a better choice if you are considering taking this course individually.

创建者 John H

•Jan 28, 2020

The pace of this specialization increased rapidly with this course. It of course makes sense that as the specialization goes on, the coursework would become more challenging and require more time. However, this was such a leap from previous courses that I feel as if it should be in a different specialization. In every lesson, I felt inundated with complex calculations and formulas that were way above my head. I think that this course spend way too much time on theory (and breezing through it!) and not enough time on R. Why not walk us through multiple Bayesian examples in R? That would actually be helpful. As is, this is a course that I needed to sog through for the specialization. One star.

创建者 Alois H

•May 21, 2017

After a brilliant start of the specialization with courses Introduction, Inference and Regression, the Bayesian course comes as a harsh disappointment.

Weeks 1 and 2 give a useful introduction to Bayes' rule. However, I haven't learnt anything of significance after that. The main instructor's explanations are unclear, and in almost every single video there's a point where there's just too much confusion to get the overall message. This is extremely frustrating and, as mentioned, in sharp contrast to the other courses.

In my opinion this course would urgently need to be re-recorded. Preferably, with a lot more input from Dr Cetinkaya-Rundel, who's an extremely gifted teacher.

创建者 Chengyu H

•Jul 21, 2016

I don't understand how come this course can get such high reviews. My experience with this course is horrible. First of all, most quiz are poorly designed, lots of mistakes. For instance, there are 10 Qs in week 1, 3 of them have mistakes. Wasted me tons of times.

Lectures are also difficult to follow. Instructors usually just give formulas without further explanation. I forced myself to go through them until week 4, I finally give it up. I feel like it is a waste of my time. I need to find a better course on this topic.

Most coursera courses are very well designed. This one is the worst I have ever experienced.

创建者 Erik F

•Jun 19, 2017

Unlike the previous sections in this specialization, this one has no reading material, nor does it have many problem sets to solve. You will definitely need to find external resources in order to complete this section, because numerous concepts are glossed over, explained vaguely, or explained poorly. I recommend Kruschke's "Doing Bayesian Data Analysis" as a very accessible way to learn Bayesian statistics. I'd have no confidence using Bayesian approaches in practice from only the material taught in this section. Frankly, this section seems like it was hastily thrown together, and I was very disappointed.

创建者 Eszter A

•Sep 13, 2016

This course needs much more work from instructors before it gets offered to the public. It is poorly assembled, offers hardly comprehensible material with no or very few resources to turn to. Reading material is listed, but they are useful for people already skilled in Bayesian Statistics. Exercises are worded such, that even the questions are a challenge to understand. Quizzes contain material never mentioned during lessons. Discussion forums are left unanswered by the teaching staff - or if they reply, they do it in a very negligent manner. No support on the merits. A major disappointment.

创建者 Graham G

•Oct 1, 2019

This course is awful, especially compared with the rest of the courses in the specialization. I had to read an entire Bayesian statistics text book in order to understand this area, and this courses still made little sense. This specialization is supposed to be for beginners and yet this course gets into intense mathematical notation with no preparation or guidance. I have somewhat of a math background, and this course was not only extremely difficult to finish, I don't feel like I really learned much of anything at the end. This course needs to be redesigned from the ground up.

创建者 Marina C R

•Jul 31, 2017

Unlike the first 3 courses of this specialization, which were excellent, this one is not recommendable at all. As many other students have reported, the teaching material is not enough neither to understand the subject nor to do the graded material. I am really disappointed because the problem seems to come at least 4 months ago but the teacher (which by the way is far to be as good as Mine) has not replied. Instead, mentors have suggested to use the forums to make questions but it is neither affordable nor acceptable.

创建者 Renat M

•Sep 8, 2017

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. In this sense watching Youtube videos and reading papers was much more helpful than the entire course itself.

创建者 Cindy C

•Feb 5, 2017

This class assumes a lot of statistical knowledge and background that is not covered in the first three classes of the series. So much statistical terminology and jargon was used by the instructor, it felt like taking a class in another language where I had to constantly stop the video and google for the terminology she used. It took a lot of grit to finish the class, which was overall a very demoralizing and negative experience.

创建者 Santiago R

•Sep 16, 2020

The material has not enough contextualization. The explanations are way to superficial. Its not necessary to explain everything, but even the intuition is lost. The teachers dont help: except from Çetinkaya-Rundel the others read from a telemprompter and one even has to wonder if they know what theyre saying. It seems that theyre more worried to dont loose the pace of the teleprompter than to convey meaning.

创建者 Ilya P

•Sep 13, 2017

While the first 3 courses had ample examples, guided practices, and other tools to learn, this course does not. Quizzes do not have good explanations, and videos do not have guided practice. There is no book to follow, hence, learning the material is difficult.

Instructors need to rework the course to include books, guided practices, and guided R examples in order to aid comprehension.

创建者 Justas M

•Sep 16, 2020

Absolutely useless and not at "beginner" level as compared to the rest of specialization. This one part requires reading almost as much as all other parts in specialization combined. Videos=textbook read in front of camera. There was not made clear, why Bayesian approach is more useful than frequentialist approach in real world statistical analysis.

创建者 Ben R

•Apr 8, 2018

A frustrating course, especially when compared to the other courses in this specialization. Lectures alternated between over my head and not giving enough information. Projects seemed designed for someone with a better grasp of R. I will probably look for another course on Bayesian statistics, because I feel my grasp of these concepts is still weak.

创建者 Michael F

•Sep 21, 2020

The information felt purely academic. I know we were show how professionals have used this type of analysis before, but those examples were way more advanced than the scope of this course. Moreover, the scope of the course was too broad. More information on how to model non-linear data would have been more valuable than this.

创建者 Andrew O

•Aug 11, 2017

The change of instructors negatively affected this class. The new instructors are nowhere near as good at explaining the data and tending to start talking about things without even explaining what they where to to use a lot of activations, which one would need to continually look up.

创建者 Naren T

•Dec 26, 2019

Very poor explanation in week 3, the new professor is not explaining the definitions or the use of them properly. Too many jargons.

Professor doesnt explain the use of prior predictive distribution and just introduces the formula without any consideration for explanation

创建者 Yu-Chi B

•Oct 12, 2020

No efforts on maintaining the quality of assignment. You will be hard or never to finish them.

Too much information concentrated in one course without clear elaboration. It should be separated to 2~3 courses.

创建者 QIAN Y

•Jul 29, 2016

The course lacks of explanation and it's very difficult to follow. It seems that the instructor just reads the slides without reasoning and explanation. Suggested reading materials are needed.

创建者 Vishnu

•Jun 30, 2019

A huge leap from the other courses in the specialization, which are all extremely well-constructed. Terms are not introduced and explained properly, and the whole course seems very haphazard.

创建者 Adrian C

•Feb 15, 2018

1St problem speed of teaching, also other students complained

2With such a speed, material was too condensed for such a broad subject

3Not sufficient explanations for a statistics beginner

创建者 Tom D

•Aug 5, 2016

This course is not well-presented. Lectures are unimaginative, and there isn't enough supporting material or readings.

创建者 Paul J

•Jul 2, 2017

Quizzes are not related to videos. There is very limited practice problems (the best way to learn math subjects).

创建者 Chen Z

•Oct 25, 2016

I get really frustrated when the tutor doesn't explain lots of concept/symbols in the materials.....

创建者 Ashish C

•Aug 29, 2019

The quality of teaching was drastically down as compared to other courses.

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