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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

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106 revisiones

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 revisiones

JH

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!!!

KD

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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26 - 50 de 105 revisiones para Bayesian Statistics: Techniques and Models

por dhirendra k

Jul 15, 2019

Very good part II course in continuation with course I. The trainer provided good and detailed explanations throughout the course. Also lot of scenarios covered with help of practical examples. Very much recommended course in Bayesian Theory

por Ujjayini D

Aug 11, 2020

Wonderful to have a course like this. Thanks to my instructor for being so thorough in teaching the materials and the Capstone project was really helpful to get through it totally. A special thanks to my peers also who reviewed my project.

por Siddaraja D

May 30, 2020

These 2 courses very good and informative for the one who is new to Bayesian statistics. I liked this course hands on portion in R. it really gave a handle on theory applied in practice. Thanks for making these courses available.

por 唐茂杰

Jan 06, 2020

It's good. In this course, professors will guide you on how to build a Bayesian model hand by hand with R. Furthermore, all prior knowledge got from another Bayesian Statistics course can get improved and solid too

por Snejana S

Apr 05, 2018

This is the most detailed course in practical Bayesian methods that I have seen. I have finally understood concepts I never grasped before. The homework assignments are definitely involved but doable AND enjoyable.

por Юрий Г

Aug 28, 2017

Excellent course, with deep explanation of difficult topics in Bayesian statistics and Marcov chain applications. Good quizzes and enough time to complete them. Recommend to all interested in probability theory.

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 Sandip D

Aug 31, 2020

Just finished this course. This course is very good to learn and provides good insight into MCMC methods and JAGS. A little work is needed from the learner's side for this course to be very successful.

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 Farid M

May 04, 2020

I really liked the course. It was well organized. The fact that the theory was accompanied by hands-on exercises in R truly reinforced the concept. Well-done!

por Xi C

May 10, 2020

Great course. The instructor provided detailed code examples and clear explanations for model intuitions. The final capstone project is a plus.

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 Rishi R

Sep 01, 2020

One of the best practical math courses present in coursera. Loved the course and will surely look upto the next course eagerly.

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 Manuel M S

Aug 20, 2020

Excellent course for introducing yourself to Monte Carlo Methods applied to Bayesian statistics. Highly recommended!

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 Russell N

Apr 27, 2020

Fantastic course that I was able to immediately incorporate into my work. Great mix of theory and hands on coding!

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 William V B

Jun 20, 2020

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

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 Ian C

Jun 17, 2020

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

por Sharang T

Aug 16, 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

Jan 29, 2019

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