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

4.8
stars
494 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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101 - 125 of 171 Reviews for Bayesian Statistics: Techniques and Models

By Razik R M T

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Jan 14, 2021

Great explanations. The instructor made it so easy to understand.

By WN S

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Oct 16, 2021

very good course, everything clearly explained; superb lecturing

By Wu S Y

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Mar 19, 2023

Detailed explanations and informative examples in R provided.

By Emma S

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Nov 20, 2020

I absolutely loved this course! Challenging and interesting!

By Stephen B

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May 29, 2019

Best course done to date. I wish they had one in STAN too!

By nicole s

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Nov 7, 2017

A great course, very detailed and a very good instructor!

By Paramita C

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Feb 28, 2021

The material was excellent and the videos were awesome!

By Suci A

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Apr 22, 2024

I am very happy joining this class, very interesting.

By Ilia S

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Sep 24, 2018

I found this course very interesting and informative.

By Ken A

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Jan 27, 2020

Excellent course. Streamlined but extremely useful.

By Hsiaoyi H

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Jul 31, 2018

Great course to learn both theories and techniques!

By Anuj K P

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Aug 1, 2020

ONE OF THE BEST COURSE FOR BAYESIAN STATISTICS .

By Arkobrato G

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Nov 11, 2019

Great course with challenging assignments and de

By Enrique A

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Nov 7, 2020

Thanks Teacher Matthew Heiner, Thanks Coursera.

By Lau C

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Apr 15, 2019

Super clear and easy to follow. Thanks so much.

By Tibor R

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Apr 20, 2019

Very good and useful course, and hard as well.

By Victor Z

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Jul 30, 2018

A very good practical and theoretical course

By Farrukh M

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Jul 25, 2017

I appropriate the way the course is taught.

By GABRIEL

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Oct 19, 2020

Very nice course, simple and comprehensive

By Yaoxiang N

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Feb 4, 2024

Very nice course for Bayesian statistics!

By pritam s

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Jul 24, 2021

I have learned a lot from this course

By Evgenii L

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May 2, 2018

A very good course to introduce yours

By Luis H

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Jul 30, 2017

Rather useful and easy understanding

By Jose F

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Feb 11, 2018

Very challenging but interesting!

By Nikola M

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Apr 7, 2019

one of best stats courses I had