# 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
2,168 个评分
569 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.

## 426 - Bayesian Statistics: From Concept to Data Analysis 的 450 个评论（共 557 个）

Feb 19, 2020

the notes for the lectures are missing.

In my opinion the notes, which includes the video materials could be very useful.

the course was good. I learnt some new concepts in bayesian thinking.

Sep 25, 2019

Very clear and informative. Would like a more extensive and combined reference material (PDF, so less need to lookup e.g. definitions of effective sample size for various distributions).

Dec 09, 2019

It was a good course for me to get familiar with the new perspective on statistics. Thank you!

Maybe, some extended practice exercise at the end of the course would make it even better)

Nov 26, 2016

A good course but neither notes nor lectures were not in much details. But still it was worth my time. I strongly recommend it if you want a subtle introduction to Bayesian Statistics.

Jul 07, 2017

Great course (and teacher). Assumes some basic highschool level for math. With experience in frequentist statistics, but not all the distributions this course was "easy" to follow.

Sep 19, 2017

Very straight-to-the-point course. Very dense, though, for a newbe in bayesian terms and concepts. But I definitely suggest it to undertand priors and posterior concepts. Thanks!

Nov 12, 2019

A great intro to Bayesian analysis and probability distributions. Personally I skipped the Excel content and converted the R code to python, which was itself valuable learning.

Mar 03, 2020

Es un buen curso introductorio, alguna explicaciones y deducciones matemáticas podrían explicarse mejor. Además estaría bueno que se den más ejemplos practicos en los videos.

Sep 05, 2018

I think the course would benefit by recommending a textbook that would supplement the lecture material. It's nice to have a reference to refer to after viewing the lectures.

Feb 05, 2018

This is a good course, I've learn a lot about Bayesian statistics with very little prior knowledge about this subject and even about statistics and probability in general.

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.

Apr 13, 2020

Great course with clear structure and good explanations. An overview "cheat sheet" would be nice, also some hints to literature which covers the topics in more depth.

Feb 24, 2019

A little heavy on the theory for my style of learning - would have appreciated more clear, applied examples in the lectures, but overall a good and informative course

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.