# 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
1,881 个评分
488 条评论

## 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.

## 376 - Bayesian Statistics: From Concept to Data Analysis 的 400 个评论（共 478 个）

Jan 17, 2020

Assignments are the best part of the code. Videos don't provide enough conceptual knowledge. Overall considering the intricacies of the topic its a very good course.

Jul 10, 2017

Nice explanations of the theory, however there could be a bit more written materials and the pace could be slightly slower, especially regarding the last chapters.

Mar 03, 2019

I took this course both to refresh my basic understanding of statistics as well as to learn what Bayesian Statistics was about. This course was good fit for this.

Aug 26, 2018

Though Bayesian statistics is not easy, and quite complex when dealing with prior and posterior. This class provides a good overview the the Bayesian statistics.

May 23, 2018

Intuitive course, but somewhat fast which leads students to pause and contemplate on what the lecturer had to say. Good start to get to know Baysian Statistics.

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.

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.

Mar 30, 2018

Very good introduction to bayesian statistics, but I would have liked a bit more written material to complement the videos, who were rather short and fast.

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.

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.

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.

Oct 10, 2019

The first question in Week 4 Honor Quiz, the coefficient for intercept, I got 138 which you show incorrect, would like to know the correct answer.

Jan 01, 2018

Very good intro to Bayesian statistics. I only rate 4/5 because the second week was disproportionately more difficult than the other three weeks.

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.

Nov 17, 2019

Very good method and quality of teaching, I'd recommend more solved and commented exercises for each topic exposed, before each week test.

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).

Nov 28, 2018

Need more information about linear regression, given material is not enough to understand topic and effectively find solution.

Nov 02, 2017

A bit dry overall, but I appreciate the rigor and precision, along with the practical examples in R. I learned a great deal.

Nov 04, 2017

Hi , this course opened a door for me in Data analysis. Very intuitive & must course for any person exploring data science.

Aug 28, 2019

Good course, but it could really use some PDFs with lecture notes ( as in contents of videos, not supplementary material).

Jan 15, 2017

This course has given me some good new insights into perceiving data and has got me started nicely I am very great full.

Mar 16, 2019

Good introduction and interesting topics. However, some of the model analyses are not appropriate and feels artificial.

Feb 04, 2018

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

Jul 02, 2018

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

Jul 03, 2019

Overall great course, the last part (linear regression) seems somewhat disconnected from the rest of the course.