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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
1,914 个评分
499 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.

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326 - Bayesian Statistics: From Concept to Data Analysis 的 350 个评论(共 489 个)

创建者 David N

Jul 30, 2017

It was a really well taught class and I enjoyed watching it. Unfortunately I seem to lack some basic understanding, since I am not a statistician. Therefore I had problems following the course and had to do quite a bit of research to do on my own to get long. Still, I managed to get 100% correct on all quizzes and all honours quizzes. So it seems, that if you put in enough effort, you can get 100% on the course without understanding many things. This is not to say, that this course is easy, it took a LOT of effort, but it was possible. I will now investigate further to get all of the basics. Maybe I will come back and take this course as a refresher. Other than that I can whole-heartedly recommend this course. The presented material is very well organized and and presented and Professor Lee is a really good teacher.

创建者 Megan R

Sep 24, 2016

A great introduction. I feel like I know a lot more about bayesian statistics now. But I do mostly feel like there is quite a bit I don't know, and while I passed, I feel like there is quite a bit more I need to do to really 'get it'. The professor recommended some books in a discussion forum and I'll be going through some of those next I am sure. I also feel, looking back, I should have had some additional math preparation before starting. The calculus was vaguely familiar but with the pace of the lectures, I felt occasionally lost. I would have found it helpful if there was a quick primer on calculus to know and review at the beginning of the course. All in all great course. Loved the presentation method.

创建者 Edward R

Jul 09, 2017

This course provides a solid overview of simple Bayesian models and common distributions used in those models. It also provides an initial understanding of conjugate prior distributions and non-informative prior distributions. The R code used in this course is very simple; easy for a beginner, but perhaps a bit simple if you are already familiar with programming in R and doing commonplace frequentist statistical analyses (regressions, ANOVA, etc). Overall, this course is definitely worth taking if you are interested in Bayesian statistics and need a good place to start. There are quite a bit of videos and supplemental materials which allow for a broadened understanding of the materials. Thanks, Dr. Lee!!

创建者 Aaron B

Sep 14, 2017

This is a decent course that covers an important topic that I've had a trouble finding good resources for learning about.

Pros: comprehensive coverage of the topic at a high level.

Cons: not enough examples to understand what is talked about in the lectures (especially the continuous data and prior with normal distribution lectures) and to anchor the topic in its practical uses.

I recommend supplementing this course with the MIT OCW 18-05 statistics class (I actually put this on hold and did that then came back).

If this course had a lot more practice problems with fully worked out answers it would help tremendously. I understand a sequel to this class is in the works and I look forward to taking it.

创建者 Jurriaan N

Dec 17, 2016

This course provides the student a profound understanding of the statistics behind the bayesian approach. Also, it gives some intuition for the difference between the frequentist and the bayesian approach, although that part could have been more explicit in my opinion. It would be very helpful to have more examples on the differences in using freq vs bayesian approach, the gains from using bayesian approach, examples of where the freq approach is limiting / misleading in its 'objectiveness'. More 'real life' examples instead of coin flipping examples - although easy to follow - would be very helpful as well, maybe in a consecutive course with applied bayesian statistics?

创建者 Jon I

Jun 13, 2017

An interesting introduction to Bayesian statistics and inference. Not for people with no statistical background, as it does assume you are comfortable with various distributions, expectations, variances, etc. and the 'standard' frequentist worldview (including inferential procedures such as linear regression). The material was well explained, and generally well examined, with a mixture of multiple choice understanding questions, and numeric response tasks which also serve as a very basic introduction to R (or Excel if you are crazy). It was good to see the instructor realising that a light shirt was causing problems and switching to a darker one as the videos went on!

创建者 Larry L E

Oct 05, 2016

I enjoyed the course. My background is mathematics, but not specifically statistics, though I do have a basic understanding of elementary frequentist statistics. My goal was to understand the fundamentals and uses of Bayesian statistics, having attempted that via a couple of textbooks without much success; this time, I got it!

I do have some reservations about the course. Herbie Lee spent a huge amount of time deriving formulas and methods - a few gaps (either hand waving or 'leave it to the student to finish') would have been helpful, I think. This would leave more time for examples and applications. But the course was well worth my time and effort.

创建者 Venkatesh U

Dec 02, 2017

This course covers most of the basics in a very good manner. I personally feel, the last week chapters especially regression do not connect the dots between the foundation that was laid and the resources provided were also not very helpful to fill that gap. For e.g I wanted to understand regression from the bayesian context, the session mostly focused on how to do regression in R and the not the internals of how to understand the mechanics behind from the bayesian stand. I will be helpful to introduce some content that helps the user to move from univariate normal distribution to multivariate normal distribution and explains some intuition behind them.

创建者 Lukas S

Sep 11, 2017

The course itself is wonderful, and the contents are very thoughtfully selected. I'm not a particular fan of the mirror-technique they use to shoot the videos. Basically, Professor Lee stands in front of a mirror and writes onto the mirror with text markers. On the video you see both him, and the text he writes.

His body often covers the text and generally, it is hard to read. Personally, I see no need to see the professor. Rather, I would prefer a note-taking app (white background). There, old formulas could also be replaced by LaTeX text making everything much more readable, plus there would be downloadable lecture slides automatically.

创建者 Ramon R

Mar 01, 2018

I liked that the teacher put things into perspective and showed the connections between the different concepts. I deduct 1 star, because the additional material in rare: Meaning, you have to take notes in the lectures to solve the quizzes and to have something for looking things up. Furthermore, in a few lectures it was difficult to read what the teacher was writing, because he was wearing a shirt with a too bright color. (Sounds funny, but I mean this serious ;-) ) In summary, a great lecture and perfect introduction into the concepts. The quizzes are constructed in a way, that they encourage learning rather than frustration.

创建者 Andrea P

Sep 23, 2016

The course is nice, the lectures are really clear. Professor Lee is brilliant and he often gives some excellent interpretations of Bayesian results. For example, the classic example of testing for rare diseases is explained in terms of ratio of true positives to all positives. Another example is the explanation of predictive mean for normal models, or the explanation of noninformative priors. They're all clearer than what usually found in many books. The only limit of the course is that it's strictly an introduction, thus very useful topics for applications such as hierarchical models or nonconjugate models are not covered.

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 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 Oleg

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!

创建者 Muhammad Y

Jul 30, 2017

The course helped me get started with Bayesian stats. This course is good if you have seem probability and stats (distributions, pdf, cdf etc.) and want to learn about the Bayesian interpretation. The course picks up pace from 3rd week and the final week seem a bit rushed. I thing more examples of explicit frequentist vs. bayesian interpretation will benefit the learners. Also, 4th week could really use some additional explanatory content. Thanks for this course, I learned something fun and useful! :)

创建者 Erfan A

Jun 13, 2017

This was a great introduction to bayesian statistic. I have background in Computer Science and Engineering but I have not yet been introduced to Bayesian Statistics. The Quizzes were where the learning was happening for me. Personally I learn the best when I code things up. I wish they had also included coding examples in Python (which is what I used for the quizzes) since that is one on the most popular languages for data science.

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 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 Jesse W

May 22, 2017

I feel like I have a much better understanding of Bayesian statistics after taking this course. I learned a lot, even though it didn't take very long to get through all of the class material. My only criticism is that the 4th week seems pretty scattered. It covers a lot of different topics in not a lot of detail. Ideally, this material should be broken up into 2 weeks and covered in greater depth.

创建者 Thomas F

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.

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 Joshua A

Sep 04, 2017

Excellent introduction to Bayesian statistics. More proofs would have been nice (perhaps an optional advanced material section?). The later half of the course increases quite a bit in difficulty and could use 1-2 more examples + applications. Professor did a great job and the quizzes thoroughly tested my knowledge. Overall, I would definitely recommend this course.

创建者 Diogo P

Jul 19, 2017

Great lectures. The explanation of each topic is extremely clear and avoids excessive mathematical burden. Lectures are short and concise. Quizzes or at least Module Honors could be a bit more challenging, though. It's a great course, anyway. I'll be looking forward to enroll in the next course of the sequence, entitled "Bayesian Statistics: Techniques and Models".

创建者 Francisco A d A e L

Nov 30, 2016

Very good course, with less emphasis in the videos and more on exercises and critical thinking, the way I like and learn the best. I particularly liked that the lecturer writes on a transparent vertical surface standing between him and the camera, very convenient. For those not so familiar with mathematics, this might hurt a bit but the payoff is super positive.

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!