返回到 Bayesian Statistics: From Concept to Data Analysis

4.6

1,693 个评分

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440 个审阅

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....

Sep 01, 2017

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.

Jun 27, 2018

Great course. The content moves at a nice pace and the videos are really good to follow. The Quizzes are also set at a good level. You can't pass this course unless you have understood the material.

筛选依据：

创建者 Xu Z

•Apr 07, 2017

Very concise and easy to follow to the end. The linear regression part could be more clear (i.e., with a lecture on the background).

创建者 Valentina D M

•Mar 29, 2018

Need more material on R.

创建者 Florian M

•Mar 02, 2018

Herbert Lee is great at explaining the mathematics behind Bayesian statistics. However, I think the course can improve greatly by also focusing more on context and the intuition behind the mathematics. I often found that I was able to pass all quizzes, while I did not 100% understand why I was doing what I was doing.

创建者 Somnath C

•Dec 03, 2016

I wish the last week were more explanatory. Although overall now I do have an idea. It's a good course. :-)

创建者 Rohit J V

•Feb 04, 2018

As a graduate student pursuing Machine Learning, this was a great course for me to get introduced to Bayesian Models.

创建者 Jakob W

•Mar 15, 2018

I found it to be a solid course. It has given me better grasp of the basics. I also found it a bit dry, and significant time spent on equations rather than high-level understanding. This is fine, as long as you know what you are in for!

创建者 xuening

•Jan 26, 2017

from week 3, the learning curve become steep

创建者 Katsu

•Jul 09, 2017

Great introductions to Bayesian statistics and inference. Quiz is actually not easy just by passively viewing videos, so taking notes during lectures is strongly recommended. Do not be afraid the Honor quiz...they are not so different from the normal ones.

创建者 Tuhin S

•Sep 01, 2017

Great course with easy to understand examples. One can explore deeper into the world of Bayesian statistics after completing this preliminary course.

创建者 Larry L E

•Oct 05, 2016

I enjoyed the course. My background is mathematics, but not specifically statistics, though I do have a basic understanding of elementary frequentist statistics. My goal was to understand the fundamentals and uses of Bayesian statistics, having attempted that via a couple of textbooks without much success; this time, I got it!

I do have some reservations about the course. Herbie Lee spent a huge amount of time deriving formulas and methods - a few gaps (either hand waving or 'leave it to the student to finish') would have been helpful, I think. This would leave more time for examples and applications. But the course was well worth my time and effort.

创建者 Víthor R F

•Jan 12, 2018

It is interesting learning the mathematics behind the analysis, but it could have been more complete, with a little less theory and more data analysis.

创建者 Hu S

•May 08, 2017

Overall a good course about Bayesian inference. Only suggestion would be to spend a bit more time explaining the interpretation behind the calculated numbers.

创建者 Seeun P

•Nov 11, 2017

Very Useful

It was little difficult to understand what the professor , but anyway it was good.

创建者 Muksitul I

•Jul 02, 2018

Well explained and articulated. You can apply it straight to your work problems. I really enjoyed doing the course.

创建者 Jose N d l R

•Apr 17, 2017

I think that, besides lesson 11 and 12, everything was very well explained. I was a bit confused with lessons 11 and 12 since I am not new to econometrics. Perhaps I found it confusing the theory background related to the lessons themselves. Just my opinion, very good course.

创建者 Carson M

•Oct 27, 2017

Pretty good overview of Bayesian statistics.

创建者 Xiao X

•May 27, 2018

The explanation is very in details. It would be better to have more mathematical derivation in the linear regression part besides the demonstation of using R.

创建者 David I M

•Sep 19, 2017

Satisfied with the course in general. Good investment of my time!!

创建者 Bishal L

•Mar 07, 2017

It is a nice introductory course on Baysian s

创建者 Pranesh K

•Mar 10, 2017

The course is excellent to learn all the basic stuff needed to master the technique of Bayesian Data Analysis.

创建者 Simon N

•Sep 09, 2017

This is a nice, bite-sized introduction to Bayesian inference. Helpful lecture notes are provided, alongside introductions to practical computations using R and Excel.

创建者 xu w

•Sep 03, 2017

this is a very good introductory course on Bayesian Statistics. Thought you will not learn deep from this course, it will give you a good big picture.

创建者 Edward R

•Jul 09, 2017

This course provides a solid overview of simple Bayesian models and common distributions used in those models. It also provides an initial understanding of conjugate prior distributions and non-informative prior distributions. The R code used in this course is very simple; easy for a beginner, but perhaps a bit simple if you are already familiar with programming in R and doing commonplace frequentist statistical analyses (regressions, ANOVA, etc). Overall, this course is definitely worth taking if you are interested in Bayesian statistics and need a good place to start. There are quite a bit of videos and supplemental materials which allow for a broadened understanding of the materials. Thanks, Dr. Lee!!

创建者 Megan R

•Sep 24, 2016

A great introduction. I feel like I know a lot more about bayesian statistics now. But I do mostly feel like there is quite a bit I don't know, and while I passed, I feel like there is quite a bit more I need to do to really 'get it'. The professor recommended some books in a discussion forum and I'll be going through some of those next I am sure. I also feel, looking back, I should have had some additional math preparation before starting. The calculus was vaguely familiar but with the pace of the lectures, I felt occasionally lost. I would have found it helpful if there was a quick primer on calculus to know and review at the beginning of the course. All in all great course. Loved the presentation method.

创建者 Lucas J

•Aug 28, 2017

I've always found stats kind of boring but, the material covered in this course is invaluable. Dr. Lee presents everything clearly and concisely.