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.

筛选依据：

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 Ben R

•Apr 08, 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 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 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 Cosma A

•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 05, 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 02, 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 26, 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.

创建者 Jeffrey W

•Jun 03, 2018

Unclear information, too vague, incomplete presentation of ideas.

创建者 Shubham J

•Sep 15, 2019

becomes too much confusing at times.