# 學生對 加州大学圣克鲁兹分校 提供的 Bayesian Statistics: From Concept to Data Analysis 的評價和反饋

4.6
2,753 個評分
721 條評論

## 課程概述

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....

## 熱門審閱

GS
2017年8月31日

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.

JB
2020年10月16日

An excellent course with some good hands on exercises in both R and excel. Not for the faint of heart mathematically speaking, assumes a competent understanding of statistics and probability going in

## 676 - Bayesian Statistics: From Concept to Data Analysis 的 700 個評論（共 713 個）

2017年6月29日

We still don't understand how Bayes differs to Frequentist... A worked example comparing the two at the end would have been nice.

2019年5月1日

It would have been great if more graphs had been provided, for easier visualization of the e.g. distributions, or concepts.

2019年7月24日

It would be better to add more explain about those equations and connect the math stuffs with the real world samples

2019年7月14日

It would be much better if there was a more sufficient introduction to the various distributions used in the course.

2019年7月9日

Very informative as an introduction to concepts, but nowhere near the deep dive I'm now interested in taking.

2020年5月4日

Good course!!... Additional examples of real life explained and done in R or excel will make it great

2021年6月18日

A lot of formulas and not that much interpretation. It is a good start in Bayesian concepts.

2019年9月21日

Too much theoretical than practical applications. No need to give both R and Excel videos.

2018年11月26日

Would have liked more problem solving and real-world application examples.

2020年6月15日

The workload is manageable however the homework is somewhat challenging.

2020年5月11日

Not well organized.

No sufficient materials, references, etc.

Very short.

2018年5月31日

Overall, it's Ok. but the explanation is too short and incomplete.

2017年8月24日

better to come up with more examples and more mathematical details

2019年1月1日

This course could be taught in better understanding way

2019年6月3日

For some derivations, the explanations are too sparse.

2021年5月31日

thank you my teacher

2017年4月9日

A bit too short.

2021年1月3日

I expected better teaching quality. The instructor is undoubtedly one of the bests in his area, but I personally did not like his teaching in this course. I felt he knows a lot of interesting concepts but intentionally does not teach them. The whole course was like somebody was reading from a textbook without adding any comments for students to actually grasp the concepts. In general I liked the course but I expected to learn much more from it.

2019年7月28日

It's alright because it gives you an overview of what is covered in a Bayesian Stats class, but the material is presented quite poorly and I had to do a lot of second hand reading to answer the questions. It is not particularly enlightening even and the formulas are presented without proper grounding, context, and intuition. I can recommend this only for dedicated self-studiers who already have some sort of grounding in Bayesian reasoning.

2021年4月26日

Week 4 explanations are just theoretical where professor is literally not giving any intuition and rushing through the concepts with equations which did not make any sense to me. Till week 3 I could kind follow. I did this course with the intend of giving a based for Machine Learning study and I am an thoroughly disappointed the way it ended up.

2020年12月31日

Good content. However, way of presentation is not very engaging. Presenter's voice very monotonous and free of any engagement. In my opinion, scribbling formulas to the board does not make a helpful learning experience.

2021年6月17日

A pretty standard "college-like" course with many definitions and derivations that do not help with conceptual understanding of the material. There are better tutorial/explanation videos on YouTube.

2021年6月23日

U​nsuficient explanation.

Lecturer just writes formulas without trying to explain background concepts. It is like reading a book of statistics. No way that most of the students will understand it.

2017年2月2日

Some matters were just given formulas and there was a lack of practice. The course should cover less materials or be longer to be effective in teaching.

2020年9月7日

Disappointing. Hard to follow, as concepts are not fully explained or linked. Steps in equations are often skipped without notice.