# 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
1,817 个评分
469 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.

## 301 - Bayesian Statistics: From Concept to Data Analysis 的 325 个评论（共 459 个）

Feb 05, 2019

I really liked the course.

What I think could be nice improvement would be more nsightful notes. Which means, that after every video, there should be a separate sheet with all the formulas being described in more detail, so that you can refer to them any time during quizes.

Nov 20, 2018

What I liked in the course is that it focuses on examples and solving actual problems. The quantity and the quality of the lectures is great, but what I really missed is written lectures where one can always lookup forgotten things or read details etc. Also, one thing that I think might be added easily is a reference to Mathematica and Maple's routines. I'm using Maple and it took some efforts to get on track. And finally, I think that 4 quizes per week is really too much for working people. It's true that the tests weren't that difficult, but it took me about an hour to do each, so I think 30 mins of lectures vs. 4 hours of quizzes is a bit unfair. Of course, my background in statistics is non-existent so it may be that it took me longer than average. But I think the course material could have been spread over say 6 weeks for lighter load on the students. All best to the team!

Nov 10, 2018

It was my first Bayesian course. Good introduction! However more accent should be placed on intuitive understanding rather than mathematical formalism. To be fair that the issue not only with this course, that the issue with 90% of all stat courses/books. As for me, I find mathematical formalism is hard to digest, intuitive understanding should come first ... May be it's just because of my limited knowledge of stats. I'll update my belief once I get better understanding of stats:) Thank you very much Dr Lee!

Nov 28, 2018

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

Jan 20, 2019

I would have given it 5 stars if some of the materials were covered more in depth (e.g. Jeffrey's prior). It seems like someone can dedicate a lot of time learning about how to apply it in different situations and in some instances I had to hunt for more in depth or simpler explanations for specific subjects (such as Jeffrey's prior) in other sources online. Overall the course is helpful and very useful and very well organized and gives a good amount of extra resources to read on but, I think it can become better if, the instructor did not rush through some of the subjects and spent more time explaining (especially towards the end of the course). The discussion forums help in these types of situations but, there will be a lot of searching dedicated to the specifics you are looking for. Overall an update to the course based on feedback of people that completed the course (from discussion forums) seems necessary. Adding an extra 5-10 minutes to some of the video contents can save the student from hours of research on the internet and confusion (sometimes due to the outside source). I'm not saying one should not spend time learning the material further from outside sources. Just saying the explanation might help avoid the confusion caused by looking into other sources.

Feb 11, 2019

Loved the theory & analytical part of the course.

Feb 22, 2019

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

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

Mar 03, 2019

Clear and consise introduction to Bayesian statistics

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.

Mar 07, 2019

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

Mar 07, 2019

a little bit difficult, I think you need to hold a solide background toward inferential statistics

Mar 16, 2019

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

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.

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.

Oct 10, 2018

Good use of R but maybe use the actual coefficient from the equations themselves rather than picking numbers pre-selected which may confuse.

Unable to look at discussion forum without posting myself.

Sep 11, 2018

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 30, 2018

Very nice introductory course, practical and to the point. Good starting point for more detailed courses

Oct 31, 2018

I found the need to search for most of the material needed to understand the lessons in other sources. Other than than it was a relatively easy class, which covers nearly the basics. This is not a tutorial on Data Analysis on R, although a short introduction is provided.

May 22, 2018

Overall the course is pretty good. They breakdown the concepts into clear and concise lectures. My only grip, is that the quizzes occur a little too frequently. They really interrupt the flow of the class. I would definitely prefer them spaced in 30-60 minute interval.

Jun 29, 2017

Very good course, I may have been at a bit of a disadvantage because I came from a behavioural sciences background rather than a full statistics or math background. It was interesting though, and I think I acquired the requisite skills to conduct a Bayesian analysis in future. However, at some points in the class it does become very formula heavy, which I did find tough to grasp at some points.

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.

Jan 15, 2018

I could grab the concept of Bayesian statistics but did not find the course fully self-contained. I had to look elsewhere to fully understand details. More complete supplementary material could help a lot.

Jan 11, 2018

A little hurry in the normal distribution part, otherwise a great course for Bayesian introduction.

Sep 04, 2017

The course was excellent !...Giving a good overview of the basics needed to navigate through this topic. However, it would have been really great if some specific examples with respect to medicine and public health practice were incorporated