Chevron Left
Back to Bayesian Statistics: Techniques and Models

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

4.8
stars
492 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

JH

Nov 1, 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!!!

CB

Feb 15, 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:

76 - 100 of 171 Reviews for Bayesian Statistics: Techniques and Models

By Stephen

•

Mar 18, 2019

Fairly good introduction to basic Bayesian statistical models and JAGS, the package to fit those models.

By Tomas F

•

Sep 19, 2021

I really, really enjoyed this course. So much so, that I'm definitively going to take the next one.

By Chow K M

•

Apr 21, 2021

The hands-on application with guidance helps one navigate between understanding and implementation.

By Cardy M I

•

Jan 29, 2019

This course helped me to get some experience at building Bayesian models and how they are applied.

By Nirajan B

•

Jan 17, 2021

Amazing course. Never taken a course of such an impressive level at coursera. Highly recommended.

By Madayan A

•

Sep 4, 2019

Very good course, a little bit to slow at some point but this is marginal in the overall feeling.

By Jaime A C

•

Jan 10, 2022

Excellent material, top quality instructor and very well designed course. I've learned a lot.

By Sariel H

•

Nov 30, 2020

Very comprehensive and practical. The course requires some experience with R programming.

By Yuanjia Y

•

May 20, 2020

This course taught very practical techniques which can be immediately applied to my job.

By Dongliang Z

•

Feb 5, 2023

Great Course. I learned the idea of MCMC. The R codes are very helpful for me. Thanks!

By Maurice

•

Apr 16, 2024

Nice teachers, good tempo, well-dosed exercises. I liked this course a lot! Thank you!

By Haozhe ( X

•

May 27, 2020

Great course. Really enjoy the capstone. Got some hands-on Bayesian Modeling analysis

By Bo Z

•

Sep 28, 2022

I did learn a lot concerning how to put Bayesian analytical skills into pratice.

By Johan F R

•

Aug 2, 2021

I highly recommend this course. Content and instructors are excellent. Thank you.

By Rodrigo G

•

Jan 25, 2021

This course is perfect. I helped me with serious research at the lab I work for.

By Jader G

•

Dec 21, 2023

Very good. I learned a lot about Bayesian statistics and modeling. I recommend!

By JOSE D J N R

•

Aug 11, 2020

A great course, both regarding theoretical explanations and practical details.

By Adolfo C C

•

Feb 18, 2021

An excellent and demanding course. High level teachers and very good material

By Jayanand S

•

Sep 17, 2019

Complex subject made easy with easy to understand theory & practical examples

By Víthor R F

•

Apr 10, 2018

Very cool, probably the best course I've done in Coursera. Keep rocking! :)

By Gustavo M

•

Aug 26, 2019

Very nice course. A bit more theory on sampling methods would be welcome.

By Alejandro D O

•

May 13, 2020

Excellent, balanced (theory and practice) course. I enjoyed very much.

By Peter W

•

Aug 9, 2020

Very pleased with the course. It was well worth the time and effort.

By nicholas t

•

Sep 6, 2018

Very thorough instruction. Excellent feedback and support on forums.

By Ahmed M

•

Nov 12, 2018

If you want to become good in modelling it is recommended to enrol.