返回到 Bayesian Statistics: Techniques and Models

4.8

245 个评分

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67 个审阅

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!!!

Jul 08, 2018

This is a great course for an introduction to Bayesian Statistics class. Prior knowledge of the use of R can be very helpful. Thanks for such a wonderful course!!!

筛选依据：

创建者 Igor K

•Jun 13, 2017

This course is a perfect continuation of the Bayesian Statistics course by Prof. Herbert Lee. It's not only mathematically rigorous but also very applied. Excellent for the beginners to the Bayesian Statistics as it allows to start confidently using Bayesian models in practice.

Matthew Heiner is an excellent lecturer. Thank you.

创建者 Oaní d S d C

•Jun 07, 2018

Excellent course. R usage straight from the beginning, a much useful addition to the previous course. It's very complete and when something mentioned and not explained further additional sources are recommended. Lot's of practical work and the final project I found amazing, a very practical approach that should prepare you to write reports and seriously analyse data. I would just recommend to put in the course prerequisites some basic R and some experience with statistics and probability. Although the course can be taken in isolation, the previous one is almost a prerequisite (if bayes thinking is new to you)

创建者 Dallam M

•Jun 27, 2017

great course

创建者 JOSE F

•Feb 11, 2018

Very challenging but interesting!

创建者 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.

创建者 Yiran W

•Jun 11, 2017

Very helpful!

创建者 Ahad H T

•May 02, 2018

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

创建者 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.

创建者 Evgenii L

•May 02, 2018

A very good course to introduce yours

创建者 Thaís P M

•Jul 01, 2017

Very good curse!!

创建者 Farrukh M

•Jul 25, 2017

I appropriate the way the course is taught.

创建者 Benjamin O A

•Jul 08, 2018

This is a great course for an introduction to Bayesian Statistics class. Prior knowledge of the use of R can be very helpful. Thanks for such a wonderful course!!!

创建者 Luis H

•Jul 30, 2017

Rather useful and easy understanding

创建者 Nicholas W T

•Sep 06, 2018

Very thorough instruction. Excellent feedback and support on forums.

创建者 Ilia S

•Sep 24, 2018

I found this course very interesting and informative.

创建者 Ahmed M

•Nov 12, 2018

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

创建者 Dongliang Y

•Sep 30, 2018

Great class.

创建者 Hsiaoyi H

•Jul 31, 2018

Great course to learn both theories and techniques!

创建者 Harshit G

•May 09, 2019

Great course.

创建者 Lau C

•Apr 15, 2019

Super clear and easy to follow. Thanks so much.

创建者 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.

创建者 Tibor R

•Apr 20, 2019

Very good and useful course, and hard as well.

创建者 Stephen B

•May 30, 2019

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

创建者 Luis A A C

•Jun 06, 2019

Excellent course.

创建者 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