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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.

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401 - Bayesian Statistics: From Concept to Data Analysis 的 425 个评论(共 458 个)

创建者 Eddie G

Apr 21, 2019

It would have been better to have more data analysis applications

创建者 Yahia E G

May 04, 2019

Very good course for beginning bayesian inference. The syllabus is easy to follow, but I also think one could benefit even more by complementing the lectures with other sources (books or other youtube explanation)

创建者 Piotr G

Jun 17, 2019

Very high quality course. Could use some modifications (e.g. few more applied examples for regression using specific priors, MCMC etc.) and implementing some simple metaphors to introduce some topics before jumping into the maths.

创建者 Robert G

Jul 03, 2019

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

创建者 Darjo

Jul 09, 2019

Most of the stuff is explained quite well and I managed to understand it. I am quite satisfied overall and I am glad I completed the course. The exercises, however, were somewhat boring. I wish there were some optional exercises that are more challenging and require you to solve more realistic problems. I also wish there were more additional materials with more in depth theory and examples of how they use these concepts for solving problems that are actually of some use. I feel like these improvements would make the course much more interesting and engaging.

创建者 Arasch M

Jul 07, 2019

The course helps in developing a quite sound grasp of the Bayesian approach to the world. The assignments are feasible and help in gaining a deeper understanding of each subject. However there is a caveat: You definitely need to review your math skills before starting this course (esp. calculus, arithmetics and combinatorics) otherwise you'll be struggling with the particularities !

创建者 Lee V

Jul 12, 2019

The lectures were good but rattled-along at quite a speed, even with pausing and "rewinding" I still found it difficult to follow, esp towards the end. I think a short explanation at the start of the video explaining what was going to be covered, what its role was and where it fitted into the big picture might have helped (background is UK maths A-level 45yrs ago and a career on the fringes of science)

创建者 Aditya D

Jul 17, 2019

The course itself is well structured and covers a lot of material.

There are points in the course where the order of reading material and videos needs to be switched. Also, it would help to update some videos with a little more explanation. It appears as if the lecturer is skipping steps.

创建者 George K

Jul 30, 2019

Really enjoyed the course! Thank you. I would have given a higher rating if: 1) the instructor had spend more time on the intuition underpinning different derivations, 2) provided more context, 3) discussed more examples from practice. However, I am definitely continuing on to "Bayesian Statistics: Techniques and Models"! Thank you once more, team UCSC!

创建者 Jan J

Aug 28, 2019

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

创建者 Michael M

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).

创建者 Thierry C

Oct 01, 2019

The course was well explained and there were several exercises pushing the learner to understand the logic behind the mathematical concept. I think it is a suitable class for people with already a certain level of statistics knowledge, even though all concepts are well explained.

创建者 Yalong L

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.

创建者 Zhenkai S

Oct 08, 2019

The course is in general well structured. The professor used a lot of mathematical equations to explain the contents. I have no problem understanding them. Everything goes smoothly, until the last section: Bayesian Linear Regression (BLE). In the last section, the professor skipped all the mathematics aspects and rushed the content with R / Excel examples. This is not what I expected. Overall, I will rate the course 4 stars.

创建者 Mohd S K

Nov 19, 2019

Course covers the concept in a very simple way. Examples and assignments are very good.

However some of the statements made throughout the lectures needs more explanation , the course did not dedicate any videos to get familiar with terminology related to probability.

创建者 Massimo G

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.

创建者 Lucas M

Nov 18, 2019

It was a very nice course that got more practical towards the end. The only thing I found a little bit confusing is the regression part, without theory videos and with practical outcomes that are exactly the same as frequentist approaches.

Don't be discouraged if you come from a background where integers and derivatives are not usual! I come from psychology and I found it a little bit hard at the beginning, but if you put effort you will get to understand almost everything. As long as you get the idea of where things like formulas are coming from and why are they done that way I think it is enough.

创建者 Colin J

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.

创建者 Danil G

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)

创建者 Ala R

Jan 01, 2019

This course could be taught in better understanding way

创建者 Francesco L

Feb 01, 2019

The topic of the course is very interesting and the subject warrants it. Yet, especially the coverage in the last week of the course appears to be shallow and too many concepts are pushed down as valid or true without a lot of theoretical justification. Besides, some of the interesting conclusions are part of the quizzes rather than an integral part of the lectures. I also think that a course like this should allow the students to receive more written material in the form of PDF files that would cover all the matters being explored. What is made available is fragmented and does not cover all the topics in an organic fashion. I believe the course could be improved substantially.

创建者 A A

Nov 26, 2018

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

创建者 sokunsatya s

May 31, 2018

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

创建者 Olexandr L

Jul 01, 2017

It was quite difficult to learn from just the material provided here, and I had to look for info on the web. Also, adding modern real life examples and going into detail would make this course better

创建者 Alessandra T

Jun 30, 2017

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