Bayesian Statistics: From Concept to Data Analysis(으)로 돌아가기

4.6
별점
2,920개의 평가
759개의 리뷰

## 강좌 소개

This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach as well as how to implement it for common types of data. We will compare the Bayesian approach to the more commonly-taught Frequentist approach, and see some of the benefits of the Bayesian approach. In particular, the Bayesian approach allows for better accounting of uncertainty, results that have more intuitive and interpretable meaning, and more explicit statements of assumptions. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. For computing, you have the choice of using Microsoft Excel or the open-source, freely available statistical package R, with equivalent content for both options. The lectures provide some of the basic mathematical development as well as explanations of philosophy and interpretation. Completion of this course will give you an understanding of the concepts of the Bayesian approach, understanding the key differences between Bayesian and Frequentist approaches, and the ability to do basic data analyses....

## 최상위 리뷰

GS

2017년 8월 31일

Good intro to Bayesian Statistics. Covers the basic concepts. Workload is reasonable and quizzes/exercises are helpful. Could include more exercises and additional backgroung/future reading materials.

JB

2020년 10월 16일

An excellent course with some good hands on exercises in both R and excel. Not for the faint of heart mathematically speaking, assumes a competent understanding of statistics and probability going in

필터링 기준:

## Bayesian Statistics: From Concept to Data Analysis의 752개 리뷰 중 201~225

교육 기관: Eben E

2020년 4월 12일

This was a were educational course. I had trouble understanding R programming but with this topic, most of the programs became more clear to me.

교육 기관: Cooper O

2017년 6월 27일

A Fantastic course. Detailed learning materials, Lots of opportunities to test your knowledge, and difficult enough to make you learn something!

교육 기관: Nitin K

2017년 6월 1일

I loved everything about this course. It reminded me of my time in school. Papers and pencils. I look forward to attending the follow up course.

교육 기관: Tiannan S

2020년 7월 6일

As a computer science student, I feel Bayesian approach is much more intuitive and more computationally friendly than the frequentist paradigm.

교육 기관: Fernando D L

2019년 3월 11일

It's a good course to know the principal concepts of Bayesian statistics. Also, the course has excellent examples to understand thew concepts.

교육 기관: O K

2018년 3월 2일

I really appreciated the content, and the way it was taught by Prof. Lee. His explanations were intuitive, without loss of mathematical rigour.

교육 기관: Giovanni G

2020년 7월 29일

Consistent and mathematically dense. If you want to go through every passage this course gives you solid understanding of Bayesian statistics.

교육 기관: RIcardo G M

2019년 12월 15일

Very good course. Concepts are very well explained, and quizzes are really helpful to apply and further

understand the explanations provided.

교육 기관: Kuntal B

2019년 11월 13일

Thanks, Coursera. This is a good course. It would be helpful if we get any proper class notes on Jeffrey's prior and Multivariate regression.

교육 기관: Artem B

2019년 7월 3일

Great course with a lot of simple, but illustrative exercises. It may be useful to have some basic prior knowledge of econometrics/statistics

교육 기관: Michael W

2019년 1월 16일

Great introductory course. It was challenging but doable for someone who has not take college level mathematics or statistics in a few years.

교육 기관: Robert K M

2018년 2월 11일

Invaluable. Excellent quizzes. A few terms could have been better defined, and a few more examples wouldn't hurt, but overall excellent.

교육 기관: Damian C

2016년 11월 10일

Very well presented course. Interesting and intuitive introduction into the fascinating Bayesian world.

Many thanks and congratulations!!!

교육 기관: Howard H

2021년 10월 6일

Excellent introduction to Bayesian statistics -- lectures, readings, and quizzes provide excellent support to learning the main concepts.

교육 기관: Ariel A

2017년 10월 12일

Great course, it has the right proportion of theory and practice. It's a great start for anyone who wants to dive into Bayesian Analysis.

교육 기관: Hari S

2020년 2월 5일

Thought is a simple manner. Made complex concepts look very easy. Would surely recommend this course. Thanks Prof. Herbert Lee and team.

교육 기관: Vignesh R

2018년 10월 8일

Awesome course that helped me overcome the Bayesian statistics way of thinking hurdle. Now, I want to go on and learn MCMC, Metropolis !

교육 기관: Qinyu X

2020년 2월 2일

The course is generally great. Nonetheless, it is not recommended for those without a statistical background and knowledge of calculus.

교육 기관: Naseera M

2017년 2월 12일

Very good course. Prof. Lee explains each concept well. Bayesian Stats makes more sense to me now than before!!

Thanks so much Prof. Lee

교육 기관: Gustavo C

2018년 10월 4일

I loved this course, I learned a lot and I hope I will be able to use this knowledge when I go back to college for my Master's degree.

교육 기관: Evgenii L

2018년 5월 2일

A very good course. Even better if you continue with the 2nd course that teaches about how to implement Bayesian data analysis in JAGS

교육 기관: Joseph G

2016년 12월 18일

I enjoyed the lecturer, the material is relevant, and the tests are well tailored to ensure you are absorbing the correct information.

교육 기관: Rodrigo G

2020년 1월 16일

Give you great insight. Very intuitive. Although we went through the last week rather quick (more explanation would have been better)

교육 기관: Jenna K

2019년 5월 13일

The lectures are at the right pace; concise and challenging. Great examples. Thank you so much for providing us with great materials.

교육 기관: Matthew S

2020년 4월 5일

Pretty challenging course. Well organized and well delivered. I learned from the exercises and also the feedback from the exercises.