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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

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497 条评论


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.


426 - Bayesian Statistics: From Concept to Data Analysis 的 450 个评论(共 487 个)

创建者 Abhimanyu R

Feb 22, 2019

This is a good course if you know probability and want to practices

创建者 Kamil S

Apr 29, 2018

Excellent course, but the lack of the written notes is a big minus

创建者 David I M

Sep 19, 2017

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

创建者 Eddie C

Jan 09, 2020

Quite harsh but give me some insight on prediction and estimation

创建者 Eddie G

Apr 21, 2019

It would have been better to have more data analysis applications

创建者 Chunhui G

Mar 07, 2019

These are a lot of stuffs that the professor didn't say clearly.

创建者 Aravind M

Apr 17, 2019

Good introductory course. Could provide more hands-on examples

创建者 Wate S

Dec 23, 2017

For me Chinese, it 's not easy to understand the quiz.

创建者 Gil S

Mar 03, 2019

Clear and consise introduction to Bayesian statistics

创建者 Yuanruo L

Nov 05, 2016

Good and simple introduction for Bayesian statistics.

创建者 Sunsik K

Aug 24, 2017

well instructed basic course of Bayesian statistics.

创建者 Alexei M

May 13, 2018

More examples are required as well as more practice

创建者 Venkataraghavan P K

Feb 11, 2019

Loved the theory & analytical part of the course.

创建者 Bishal L

Mar 07, 2017

It is a nice introductory course on Baysian s

创建者 Carson M

Oct 27, 2017

Pretty good overview of Bayesian statistics.

创建者 xuening

Jan 26, 2017

from week 3, the learning curve become steep

创建者 Wenbin M

Feb 09, 2020

The normal distribution part lacks detail.

创建者 Ezra K

Feb 13, 2020

Good overview of Bayesian statistics.

创建者 Xindie H

Jan 27, 2019

Nice and easy introduction course.

创建者 Witold W

Aug 29, 2017

Liked it and can recommend it.

创建者 Chuck M

Jan 11, 2017

A good course - recommended.

创建者 Valentina D M

Mar 29, 2018

Need more material on R.

创建者 Spyros L

Sep 20, 2017

Very good introduction!

创建者 Johannes M

Jun 06, 2017

I am working in the field of epidemiological, medical research. Overall I would recommend taking this course. It needs to be pointed out, however, that if you are outside of the field of mathematics this specific course entails a lot of research (using google etc) that needs to be undertaken to understand the course material. Maybe in the future the course directors can compile a summary of all important formulae etc so that professionals from sectors other than mathematics can follow more easily and can focus much on this particular course on Bayesian statistics and not so much on conducting additional research to understand the basic course material. Furthermore, alongside a summary formula sheet it would be good to have all explanations included, what the parameters (alpha, beta etc) stand for with regards to the specific context. Thank you very much for this course!

创建者 Leandro G G

Oct 22, 2019

This course provides a good overview to Bayesian statistics, but a larger dose of explanations of would be very useful. Mr Lee discusses, in the beginning, the differences between frequentist and bayesian paradigm. I feel that this would be beneficial in the other parts of the course, too. I feel that many of the lectures simply go too fast. After lectures full of Math, it would be useful to present lectures analyzing what had just been taught, in order to better grasp the content. And in general, this happens through the whole course - most lectures are basically math, without much time for grasping the intuition and underlying logic. For example: in the final part, under linear regression, it might be be difficult to grasp what a bayesian predictive interval means. All in all, I recommend this MOOC, but you might find hard to fully grasp it.