Chevron Left
Back to Bayesian Statistics: Techniques and Models

Learner Reviews & Feedback for Bayesian Statistics: Techniques and Models by University of California, Santa Cruz

444 ratings

About the Course

This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces Bayesian methods through use of simple conjugate models. Real-world data often require more sophisticated models to reach realistic conclusions. This course aims to expand our “Bayesian toolbox” with more general models, and computational techniques to fit them. In particular, we will introduce Markov chain Monte Carlo (MCMC) methods, which allow sampling from posterior distributions that have no analytical solution. We will use the open-source, freely available software R (some experience is assumed, e.g., completing the previous course in R) and JAGS (no experience required). We will learn how to construct, fit, assess, and compare Bayesian statistical models to answer scientific questions involving continuous, binary, and count data. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. The lectures provide some of the basic mathematical development, explanations of the statistical modeling process, and a few basic modeling techniques commonly used by statisticians. Computer demonstrations provide concrete, practical walkthroughs. Completion of this course will give you access to a wide range of Bayesian analytical tools, customizable to your data....

Top reviews


Oct 31, 2017

This course is excellent! The material is very very interesting, the videos are of high quality and the quizzes and project really helps you getting it together. I really enjoyed it!!!


Feb 14, 2021

The course was really interesting and the codes were easy to follow. Although I did take the previous course for this series, I still found it hard to grasp the concepts immediately.

Filter by:

1 - 25 of 146 Reviews for Bayesian Statistics: Techniques and Models

By Jonathan B

Jan 1, 2019

By Sandra M

May 14, 2018

By Brian K

Apr 1, 2019

By Milo V

Jun 19, 2018

By Vladimir Y

Nov 11, 2017

By Toshiaki O

Nov 23, 2020

By zhen w

Jul 28, 2017

By Igor K

Jun 12, 2017

By Krishna D

Jan 9, 2020

By Eugene B

Jun 26, 2019

By Sathishkumar R P

May 21, 2018

By Jiasun L

Jul 20, 2019

By Paolo P

Mar 26, 2022

By Cameron K

Jun 7, 2017

By Tracey

Oct 6, 2020

By Georgy M

Apr 1, 2019

By Benjamin O A

Jul 7, 2018

By Seema K

Nov 17, 2019

By Arnaud D

Dec 8, 2018

By Yahia E

Jun 6, 2019

By Chiu W K

Jul 29, 2017

By Andrew M

Nov 8, 2021

By Oaní d S d C

Jun 7, 2018

By Jens K

Jun 13, 2020

By Jerry L

Jul 5, 2017