Chevron Left
Back to Bayesian Statistics

Learner Reviews & Feedback for Bayesian Statistics by Duke University

784 ratings

About the Course

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."...

Top reviews


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.


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.

Filter by:

26 - 50 of 248 Reviews for Bayesian Statistics

By Yan Z

Jun 26, 2022

By Minasian V

Aug 16, 2016

By Chin J L

Jun 7, 2018

By Chen Y

Jul 6, 2017

By Aleix D

Mar 19, 2019

By Minas-Marios V

Apr 26, 2017

By Deepthi R

May 18, 2020

By Juan R

May 30, 2021

By mausci71

Aug 11, 2020

By amin

Feb 25, 2021

By Shannon

Aug 27, 2019

By Matthew C

Jul 25, 2020

By Shivang S

Jun 18, 2020

By Alexander C

Jul 16, 2020

By Justas M

Sep 16, 2020

By daniel g e c

Jan 8, 2021

By Syed S R

Sep 13, 2018

By vacous

Jun 6, 2017

By Daniel R

Jun 14, 2017

By Andrea P

Nov 12, 2016

By Huynh L D

Jul 9, 2016

By xyshen

Sep 7, 2020


Nov 12, 2020

By Jonathan N

Oct 22, 2016

By Nazir A

Sep 20, 2019