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Opiniones y comentarios de aprendices correspondientes a Bayesian Statistics: Techniques and Models por parte de Universidad de California en Santa Cruz

4.8
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375 calificaciones
118 reseña

Acerca del Curso

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....

Principales reseñas

JH
31 de oct. de 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!!!

KD
8 de ene. de 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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51 - 75 de 117 revisiones para Bayesian Statistics: Techniques and Models

por William V B

20 de jun. de 2020

Very useful introduction to practical application of Bayesian inference to real world problems using R and JAGS.

por Artem B

25 de ago. de 2019

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

por Ian C

17 de jun. de 2020

I really enjoyed the course! Thank you for the very interesting and thought-provoking lectures and assignments.

por Sharang T

16 de ago. de 2020

It was a very informative course and it was very useful in giving an introduction to a whole new field for me

por Juan C

29 de ene. de 2019

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

por Ariel A

28 de ago. de 2017

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

por Hyun J K

13 de oct. de 2019

Perfect combination of theory part + application part

Recommend to people who took the basic Bayesian class

por Stephen H

17 de mar. de 2019

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

por Cardy M I

29 de ene. de 2019

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

por Madayan A

4 de sep. de 2019

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

por Sariel H

29 de nov. de 2020

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

por Yuanjia Y

20 de may. de 2020

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

por Maurice

20 de may. de 2020

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

por Haozhe ( X

27 de may. de 2020

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

por JOSE D J N R

11 de ago. de 2020

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

por Jayanand S

16 de sep. de 2019

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

por Víthor R F

9 de abr. de 2018

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

por Gustavo M

26 de ago. de 2019

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

por Alejandro D O

13 de may. de 2020

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

por Peter W

8 de ago. de 2020

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

por Nicholas W T

6 de sep. de 2018

Very thorough instruction. Excellent feedback and support on forums.

por Ahmed M

12 de nov. de 2018

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

por Emma S

20 de nov. de 2020

I absolutely loved this course! Challenging and interesting!

por Stephen B

29 de may. de 2019

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

por nicole s

7 de nov. de 2017

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