Volver a Bayesian Statistics: Techniques and Models

4.8

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258 calificaciones

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72 revisiones

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....

Nov 01, 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!!!

Jan 09, 2020

Excellent teacher and very well taught. Right amount of theory and programming combination. Made the subject easy to learn. Enjoyed it very much. Thank you very much.

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por Chunhui G

•Apr 19, 2019

This is a great course. Although the first course of this series is lack of organization. But this one is fantastic. The lecturer is great. Although you have to pay money to do the quiz, it is worthwhile.

por Jonathan H

•Nov 01, 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!!!

por Krishna D

•Jan 09, 2020

Excellent teacher and very well taught. Right amount of theory and programming combination. Made the subject easy to learn. Enjoyed it very much. Thank you very much.

por Danial A

•Jan 10, 2018

The best course I had in statistics. unlike many other courses the instructor does not ignore the underlying mathematics of the codes.

por Wangtx

•Dec 11, 2018

Great materials and well organized lecture structure. But in the meanwhile, it requires quite a lot preliminary knowledge.

por Dongxiao H

•Nov 15, 2017

terrific, so I've learn quite a lot basic knowledge about MCMC. So I can build kinds of models with better understanding.

por Ahad H T

•May 02, 2018

Outstanding, Excellent, Must do for statistician. I'm from Civil Engg Background easily capable to learn the course

por Vlad V

•Mar 21, 2018

Very good course giving a good practical kickoff to a very interesting and exciting topic of Bayesian statistics.

por Artem B

•Aug 25, 2019

It is very concise, but informative course. It combines both theory and practice in R, which are easy to follow.

por Juan C

•Jan 29, 2019

Muy recomendable para los investigadores y profesionales que quieren desarrollar productos y procesos nuevos.

por Ariel A

•Aug 28, 2017

This course is a great start for everyone who wants to dive into Bayesian Statistics. Very clear and helpful.

por Hyun J K

•Oct 13, 2019

Perfect combination of theory part + application part

Recommend to people who took the basic Bayesian class

por Stephen H

•Mar 18, 2019

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

por Cardy M I

•Jan 29, 2019

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

por Madayan A

•Sep 04, 2019

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

por Jayanand S

•Sep 17, 2019

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

por Víthor R F

•Apr 10, 2018

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

por Gustavo M

•Aug 26, 2019

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

por Nicholas W T

•Sep 06, 2018

Very thorough instruction. Excellent feedback and support on forums.

por Ahmed M

•Nov 12, 2018

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

por Stephen B

•May 30, 2019

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

por nicole s

•Nov 07, 2017

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

por Ilia S

•Sep 24, 2018

I found this course very interesting and informative.

por Hsiaoyi H

•Jul 31, 2018

Great course to learn both theories and techniques!

por Arkobrato G

•Nov 11, 2019

Great course with challenging assignments and de

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