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

4.8
stars
484 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

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!!!

CB

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.

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126 - 150 of 164 Reviews for Bayesian Statistics: Techniques and Models

By M S

•

Aug 8, 2023

Nice presentations

By Roberto S

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Mar 20, 2023

Very good course!

By shweta d

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Oct 22, 2022

Excellent Content

By Luis A

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Jun 6, 2019

Excellent course.

By Thais P

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Jul 1, 2017

Very good curse!!

By Neha K

•

Sep 14, 2020

excellent course

By sameen n

•

Apr 30, 2020

Amazing course.

By Clara X G

•

Aug 17, 2022

Learned a lot！

By Harshit G

•

May 9, 2019

Great course.

By Michael B

•

Dec 29, 2017

Great course!

By Yiran W

•

Jun 11, 2017

Very helpful!

By Seokkyu K

•

Jun 5, 2022

Best course!

By Aya M L N

•

Nov 9, 2020

Thanks a lot

By Larry Y

•

Sep 30, 2018

Great class.

By Dallam M

•

Jun 27, 2017

great course

By SURAJIT C

•

Dec 25, 2020

Good Work!

By Nancy L

•

Oct 11, 2019

Thank you!

By Robert d J

•

May 16, 2022

Excellent

By Owendrila S

•

Sep 28, 2020

Very Good

By JOYDIP M

•

Aug 9, 2020

helpful

By Md. R Q S

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Sep 23, 2020

great

By MD F K

•

Aug 27, 2020

good

By clement c

•

Dec 13, 2019

Awsome course overall. I took one star away for the capstone project's correction system that I think could be improved. If felt this system to be too rigid. Maybe allowing people to give points 1 by 1 intead of just a few options (0, 3 or 5 points) would help. I also feel like too many points are awarded for criterias that are beside the point of the course (5 points for the number of pages, 5 points for knowing how to write an abstract, 3 points for redacting the problem to be answered). This skills however important were not taught in this course and are unfair to evaluate in my opinion.

By Khoa M

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Oct 1, 2021

The course was really great for me to start using R and build models. But it was really challenging. And the final peer-graded submission really threw me off due to the late / lousy markings for my submission and lack of available submissions for me to mark. Still an enriching and challenging course overall!

By Henk v E

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Sep 25, 2017

I thoroughly enjoyed participating in this course, and I do think that I learned a fair number of skills of real conceptual and practical value. Thanks to the instructors' team for their dedicated efforts.