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学生对 加州大学圣克鲁兹分校 提供的 Bayesian Statistics: From Concept to Data Analysis 的评价和反馈

4.6
1,698 个评分
442 个审阅

课程概述

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....

热门审阅

GS

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.

JH

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.

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326 - Bayesian Statistics: From Concept to Data Analysis 的 350 个评论(共 432 个)

创建者 David I M

Sep 19, 2017

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

创建者 Damien P

Feb 23, 2017

Good course, but in my opinion misses of lectures/pdf to ease understanding.

创建者 Jesse W

May 22, 2017

I feel like I have a much better understanding of Bayesian statistics after taking this course. I learned a lot, even though it didn't take very long to get through all of the class material. My only criticism is that the 4th week seems pretty scattered. It covers a lot of different topics in not a lot of detail. Ideally, this material should be broken up into 2 weeks and covered in greater depth.

创建者 Artem B

Feb 07, 2018

This is a great course and I have learned a lot. The teacher is extremely knowledgeable and formulates things very clearly. However, this is really a math course. For me it was hard to stay motivated because the language of the course is mathematics, the teacher juggles with the concepts that my mind was still trying to process and absorb. I was able to finish all exercises, including the honors ones, but when I finished the week 3, I had to redo it completely again and buy a book on Bayesian statistics by John Kruschke which helped me immensely to rethink the basic concepts again. This course could be excellent if it included more reiterations of concepts, was explained in more general language, the pace was slower and most importantly included more practical applications. The typical statistical examples of coin flipping are fun, but too abstract. In the end, I want to know how I can apply Bayesian statistics. A lot of knowledge of mathematics was assumed and I had to look up a lot of concepts myself. The derivations sometimes also went too quick and supplementary materials were quite dense. I think this course is a perfect refresher course for someone who has mathematical background and has taken a Bayesian statistics course some time ago. But for the beginner with some mathematical background (I am familiar with the frequentist statistics, machine learning, calculus) it was too much of a challenge. If it were not a Coursera course, where I can rewind endlessly and work at my own pace, but a regular university course, there will be p=.9 that I would drop out, while my prior for dropping out would be p=.05

创建者 Erfan A

Jun 13, 2017

This was a great introduction to bayesian statistic. I have background in Computer Science and Engineering but I have not yet been introduced to Bayesian Statistics. The Quizzes were where the learning was happening for me. Personally I learn the best when I code things up. I wish they had also included coding examples in Python (which is what I used for the quizzes) since that is one on the most popular languages for data science.

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 Maria A

Feb 22, 2018

Good course , but contains some challenging material .Thank you Professor L

创建者 LittleStone

Nov 12, 2016

A very good course which enlights me the study of bayesian statistics, thank you.

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 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 Yuanruo L

Nov 05, 2016

Good and simple introduction for Bayesian statistics.

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 Jurriaan N

Dec 17, 2016

This course provides the student a profound understanding of the statistics behind the bayesian approach. Also, it gives some intuition for the difference between the frequentist and the bayesian approach, although that part could have been more explicit in my opinion. It would be very helpful to have more examples on the differences in using freq vs bayesian approach, the gains from using bayesian approach, examples of where the freq approach is limiting / misleading in its 'objectiveness'. More 'real life' examples instead of coin flipping examples - although easy to follow - would be very helpful as well, maybe in a consecutive course with applied bayesian statistics?

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 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 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 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 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 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 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 Pranesh K

Mar 10, 2017

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