베이지안 통계(으)로 돌아가기

# 듀크대학교의 베이지안 통계 학습자 리뷰 및 피드백

3.8
별점
719개의 평가
233개의 리뷰

## 강좌 소개

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution. Additionally, the course will introduce credible regions, Bayesian comparisons of means and proportions, Bayesian regression and inference using multiple models, and discussion of Bayesian prediction. We assume learners in this course have background knowledge equivalent to what is covered in the earlier three courses in this specialization: "Introduction to Probability and Data," "Inferential Statistics," and "Linear Regression and Modeling."...

## 최상위 리뷰

RR

Sep 21, 2017

Great course. Difficult to apprehend sometimes as the Frequentist paradigm is learned first but once you get it, it is really amazing to see the believe update in action with data.

GH

Apr 10, 2018

I like this course a lot. Explanations are clear and much of the (unnecessarily heavyweight) maths is glossed over. I particularly liked the sections on Bayesian model selection.

필터링 기준:

## 베이지안 통계의 225개 리뷰 중 76~100

교육 기관: EDILSON S S O J

Jul 25, 2016

Very Nice Course! Excellent!

교육 기관: Alexey K

May 10, 2018

The magic course...)

Thanks!

교육 기관: Harish S

Jun 21, 2018

Of an elvated level!

교육 기관: Tran T H

Sep 24, 2019

교육 기관: Long K

Mar 16, 2018

Strongly recommend!

교육 기관: Donal G

Jan 07, 2017

Very good course.

교육 기관: 李俊宏

May 22, 2017

very intuitive!

교육 기관: Tian Z

Dec 14, 2017

교육 기관: John A

Oct 02, 2019

Great course!

교육 기관: Pedro G F M

Dec 20, 2018

great course!

교육 기관: can z

Jan 10, 2018

Great course.

교육 기관: Denise L

Aug 02, 2018

Challenging!

교육 기관: Oscar C R

Aug 28, 2020

Good Course

교육 기관: Marina Z

Jun 27, 2017

Challenging

교육 기관: hyunwoo j

Jul 16, 2016

very useful

교육 기관: Riku L

Dec 23, 2017

B

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!

교육 기관: NANDAN B

Jun 14, 2020

Good

교육 기관: Byeong-eok K

Aug 01, 2017

Good

교육 기관: Sanan I

Jun 04, 2020

.

교육 기관: Whitchurch S R M

May 26, 2020

This is a good course. However, inorder to understand what the Professors are saying. I had to take a prelim course, to learn the vocabulary , as well as basic baysean concepts before attempting this course again. The course needs a certain level of accepting concepts in an abstract sense, and not being detail oriented while listening to the lectures, to gain understanding of the content. Also one needs to watch the videos again and again at a reduced speed to grasp what the professors say. This is certainly not an easy course, but the rewards are worth it. Once the student crosses a threshold of knowledge barrier. All in all this course has good content, without getting too caught up in the Math. I have not found better courses than this for Baysean Statistics.

교육 기관: Maurits v d M

Aug 22, 2016

I had a lot of fun during this course, but I think it is simply too short to present all the topics in sufficient detail. Furthermore, I took this course without doing the prior courses in the specialization, and there were a couple of moments when I really thought previous knowledge from a different course was required.

I think for the most part the lecturers did a great job in explaining the materials in the course. The lectures themselves were also well structured, and the topics followed each other in a logical order. I would have loved to spend more time on modeling techniques and Markov Chain Monte Carlo.

교육 기관: Pouya Z

Sep 26, 2019

The course was great and really informative. Particularly, it was interesting to get to work with BAS and statr packages that were developed, essentially, by the instructors. I, however, think that from decision loss functions onward, the course suddenly became way more complex. The normal conjugate families were not discussed on the previous lab, and I believe deserve to be emphasized with an example before heading to regression and reference priors. However, the notes were quite helpful. All and all, it was a great course.

교육 기관: Ravichandran V

Aug 06, 2019

Its really hard for me to follow this specific course, its as if I am reading a summary of a novel rather than a novel, ideally this course should be broken into two courses and made into two five week courses. I may need to take additional courses or read some books to get a clear understanding.

In the previous three courses the open stats book helped a lot, however, the online content for this course is difficult to follow as well.

교육 기관: Bram M

Aug 25, 2020

Great course, with good examples of how Bayesian stats work. It is incredibly difficult to follow, however, and would benefit from a more elaborate discussion of methodology (e.g. how (conjugate) priors are chosen, how to report results, etc). It currently is one long list of formulae, formulae, and formulae

교육 기관: Uira d M

Jul 03, 2019

The course is well structured but the span of topics is large and the complexity great. Maybe an extended version with more explanations and demonstrations of the equations would be better for understanding the whole concept of bayesian statistics, specially inference.