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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
2,682 个评分
699 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
Aug 31, 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.

JB
Oct 16, 2020

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

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101 - Bayesian Statistics: From Concept to Data Analysis 的 125 个评论(共 686 个)

创建者 Ruoxiao S

Aug 15, 2019

This class is pretty helpful for the beginners and the instructor has a clear organization of the lecture. The Quizzes are also a good way to know what you have mastered. I have a better and deeper understanding of the Bayesian Statistics now.

创建者 Nicholas P

Jan 13, 2018

Highly informative. Prof. Herbert Lee is a great professor providing very thorough notes and material for the Bayesian paradigm of Statistics. I would highly recommend this to any who are interested. It is also a great introduction to using R.

创建者 Michail L

Aug 4, 2019

It was an amazing course. Prof. Lee is an excellent teacher, the lectures were very interesting and illuminating, and the problems challenging and based on the material discussed. Highly recommended to get a basic idea of Bayesian statistics.

创建者 Alexis U

Jul 25, 2020

A good introduction to Bayesian Statistics. Not too deep, but you need to have some familiarity with probability notation. Also it seems it recently had some manteinance because broken links in lectures are now redirected to correct links.

创建者 Jason R

Apr 8, 2017

I found this course to be incredibly useful to learn Bayesian statistics and a useful guide for applying the information in r and excel. I would definitely recommend it to anyone interested in furthering their understanding on this topic.

创建者 Juan J O O

Jun 6, 2019

Excellent course. I learned late to use the note clipboard to take notes. At times the video lectures are hard to follow because the concepts are not easy. I had to watch the video lectures several times to fully grasp the concepts.

创建者 Luca A

Sep 22, 2018

Really interesting course, expecially in the first part, which has a simple and clear introduction where the "philosophy" of Bayesian approach is explained. Now I have some useful instrument and the curiosity for more sophisticated ones.

创建者 Ayush T

Feb 18, 2019

It's really a good course for Bayesian Statistics. Exercises are designed in such a way that they can't be passed if you've not understood the topic completely. The workload is manageable and the course content is really well organized.

创建者 Ghanem w

Feb 14, 2017

This course provide a very good understanding of the bayesian approach of the statistic. It is very accessible thanks to the learning material (pdf) provided before each lessons and which recall all the basis needed.

Thank you Herbie

创建者 Syarif M

Dec 2, 2016

Definitly the best statistic course for beginners with some mathematical knowledge. Love the way the videos are recorded (Transparent glass between the camera and teacher) it should be a standard for online course! thank you so much!

创建者 Howard H

Apr 10, 2018

A very solid introduction to Bayesian Statistics. Lectures were sufficiently detailed and of excellent quality, and the problem sets supported and reinforced the material very well. I look forward to taking part 2 of this sequence.

创建者 Muhammad Z R

Mar 27, 2021

If variables be consistent throughout all lectures, it would be great.

Shirt color was matching at some instances due to which seeing notes on lecture board was difficult.

Examples and quizzes were quite helpful for understanding.

创建者 Sergio D H

Sep 21, 2017

Great introductory course on Bayesian data analysis. The course is self-contained and the videos make a great job explaining the concepts of each lesson. I truly appreciated the practical approach either with R or Excel.

创建者 Alejandro D O

Mar 3, 2020

Excellent course. Prof. Lee is a superb teacher. The balance between class, exercices and tests is well achieved. I would certainly recommend this course to anyone aiming for a first encounter with Bayesian statistics.

创建者 Sandro P

Nov 21, 2017

Very interesting course.

For me the most interesting and important themes are about priors:

1) conjugated priors

2) effective prior size

3) how to choose a prior

4) non-informative priors

5) improper priors

6) Jeffreys priors

创建者 joari c

Feb 9, 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

创建者 Shiyang Z

Jun 12, 2020

This course is well-designed. A great introduction to Bayesian Statistics. I love the quizzes and short questions in the videos which help to understand the class materials. And the blackboard also looks cool haha

创建者 Tu L

Jan 10, 2021

This is a very helpful and concise course about Bayesian approach to statistical inference. It is suitable for anyone with little background knowledge to quickly grasp the ideas of Bayesian methods in statistics.

创建者 KK

Dec 1, 2016

Although I only spent less than one week to finish the course, I think it is quite valuable if you are interested in statistical inference and want to learn more specific in Beyesian Statistics. High Recommended.

创建者 Fabian M

Feb 20, 2018

The course manages very well to balance out comprehensibility and content. Professor Herbert Lee has obviously prepared the material very thoroughly and imparts the content of the course in an enjoyable fashion.

创建者 WU T T

Jan 13, 2018

I think the number of quiz questions is appropriate. They helped me to have better understanding of the content of this course. Teacher's lectures are brief and clear. I will take the next part of this lesson.

创建者 chenshuai

Aug 26, 2020

very helpful courses. The assignment is decent and the professor explanation is very clear. I would like it to provide a bit hint for the honor part too, since there is no answers for the honor part for now.

创建者 Padmeswar D

Jul 9, 2020

I liked the course because it is meticulously designed to help build on concepts in Bayesian Statistical Analysis. The Quiz's really helped me grasp the concepts as they fully supplement the lecture classes.

创建者 Vimos T

Aug 24, 2016

This course makes a lot of details clear to me. Thanks professor for this great course.

I still have one question, is the professor writing on a transparent board in inverse pattern? The technique is amazing!

创建者 Khoa M

Dec 17, 2020

Good introduction to Bayesian Statistics. Although I still need more time to realize how to apply the concepts into real-life situations, it definitely helps if I encounter this subject again in the future.