# 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
1,821 个评分
471 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.

## 26 - Bayesian Statistics: From Concept to Data Analysis 的 50 个评论（共 461 个）

Apr 15, 2019

Super clear and easy to follow. Thanks for the introduction.

Mar 06, 2019

Nice Course, Good Instructers

Mar 08, 2019

I recommend this course for anyone interested in learning Bayesian statistics: You can start here. It covers the core concepts as well as some computations using R and Excel.

Mar 18, 2019

A very nice introduction to Bayesian Statistics in a couple of hours. The course is quite intuitive and concise.

Dec 24, 2018

Great introduction for beginners

Feb 04, 2019

Feb 05, 2019

Thanks it was nice learning from wonderfu instructors.

Mar 11, 2019

It's a good course to know the principal concepts of Bayesian statistics. Also, the course has excellent examples to understand thew concepts.

Mar 11, 2019

refreshed university materials and also gained deep understanding of probability theorems

Sep 15, 2016

Awesome.

Nov 26, 2017

Very helpful and extremely educational. One of those rare courses I actually finished!

Dec 19, 2016

Great intro to Bayesian Statistics. The math gets complex but the professor illustrates with examples to help with understanding. The exercises are generally similar to the examples in the lectures and honestly not as hard as they could've been. The course is only 4 weeks and moves pretty fast. Although I scored well, I may take the course again to help make sure all the details and concepts fully sank in.

I'm hungry for a deeper dive into the topic. I hope there is a follow up course in the future.

Nov 11, 2017

I strongly recommend this course to those who are interested in learning theoretical concepts that build Machine Learning statistics especially Bayesian. The course content was well organized and the professor presented the concepts in a very engaging way. Relevant and appropriate examples and in-video quizzes were very helpful in understanding the theory.

Jul 20, 2017

Great for understanding the fundamentals of Bayesian analysis!

Aug 27, 2017

very good course with good concept and work. Content is very rich. Assignments are very good. It was very helpful for me. Thanks for providing such a good course.

May 10, 2017

Great course!

Dec 07, 2016

One of the best courses I took to date. Paralleled only by ML (by Andrew Ng). Non-trivial assignments, focused on practice, well-explained concepts in readings. Truly impressed.

Nov 25, 2016

Clear, concise and well presented

Sep 17, 2016

Out of 15 online courses I have taken over the last 3 years, this is the best. Professor Lee presents rather difficult material in a clear, detailed, style. The lesson quizzes are remarkably useful; it seems real care has been taken in aligning the questions with the key points in the lectures, and in furthering one's understanding of the same.

Aug 25, 2017

Fastest route to Bayesian Learning.

Jun 10, 2017

Good!

Dec 27, 2016

I really enjoyed this course. The lectures were short and clearly explained, and particularly highlighted why Bayesian statistics is different and what is useful about it. I would have like a bit more walk-through on some of the derivations in weeks 3 and 4. More R exercises and further resource recommendations would have been useful.

Feb 10, 2017

Very instructive introduction to Bayes reasoning. By attending all videos and completing quizzes, you get a reasonable understanding of the concepts and reasoning. Thanks to prof Herbert Lee and all the supporting team

Dec 26, 2017

Very useful crash course in Bayesian Statistics. It requires some basic knowledge in statistics and probability as stated.

Oct 03, 2016

The course creates great foundations for digging deeper into more complex concepts and trying to run some Bayesian statistics on simple real life problems