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学生对 University of California, Santa Cruz 提供的 Bayesian Statistics: From Concept to Data Analysis 的评价和反馈

4.6
3,221 个评分

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

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

JH

Jun 26, 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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526 - Bayesian Statistics: From Concept to Data Analysis 的 550 个评论(共 842 个)

创建者 FNU R M

Aug 15, 2019

Nice Course

创建者 Binghao L

Apr 11, 2019

nice course

创建者 Joshua C M

Oct 10, 2017

Good course

创建者 Zito R

Feb 26, 2018

Excellent!

创建者 Rigoberto J M A

Nov 5, 2017

Excellent.

创建者 Vinicius P d A

Apr 19, 2017

Very good!

创建者 CHIRRI M

Nov 23, 2024

very good

创建者 Zhaojie W

Aug 18, 2024

Very Nice

创建者 Hortensia M

Apr 12, 2021

excelent!

创建者 FERDINANTOS K

Nov 14, 2020

THANK YOU

创建者 Benjamin S K

Sep 12, 2020

recommend

创建者 Nathan W

Sep 27, 2018

Completed

创建者 Jinxiao Z

Jun 20, 2018

excellent

创建者 Fatemeh S

Dec 13, 2021

PERFECT!

创建者 shashi r

Sep 15, 2016

Awesome.

创建者 Valérie G U

Mar 20, 2024

Superb

创建者 Xinyi J

Apr 7, 2019

Great!

创建者 Anna B R

Dec 17, 2017

Great!

创建者 Li W Y

Jun 10, 2017

Good!

创建者 SUMALATHA M

Nov 24, 2023

good

创建者 Nguyễn Đ

Jan 28, 2022

good

创建者 Aarya S

Apr 20, 2025

..

创建者 Benjamin A A

May 20, 2018

j

创建者 Artem B

Feb 7, 2018

This is a great course and I have learned a lot. The teacher is extremely knowledgeable and formulates things very clearly. However, this is really a math course. For me it was hard to stay motivated because the language of the course is mathematics, the teacher juggles with the concepts that my mind was still trying to process and absorb. I was able to finish all exercises, including the honors ones, but when I finished the week 3, I had to redo it completely again and buy a book on Bayesian statistics by John Kruschke which helped me immensely to rethink the basic concepts again. This course could be excellent if it included more reiterations of concepts, was explained in more general language, the pace was slower and most importantly included more practical applications. The typical statistical examples of coin flipping are fun, but too abstract. In the end, I want to know how I can apply Bayesian statistics. A lot of knowledge of mathematics was assumed and I had to look up a lot of concepts myself. The derivations sometimes also went too quick and supplementary materials were quite dense. I think this course is a perfect refresher course for someone who has mathematical background and has taken a Bayesian statistics course some time ago. But for the beginner with some mathematical background (I am familiar with the frequentist statistics, machine learning, calculus) it was too much of a challenge. If it were not a Coursera course, where I can rewind endlessly and work at my own pace, but a regular university course, there will be p=.9 that I would drop out, while my prior for dropping out would be p=.05

创建者 Yildirim K

Jan 19, 2019

I would have given it 5 stars if some of the materials were covered more in depth (e.g. Jeffrey's prior). It seems like someone can dedicate a lot of time learning about how to apply it in different situations and in some instances I had to hunt for more in depth or simpler explanations for specific subjects (such as Jeffrey's prior) in other sources online. Overall the course is helpful and very useful and very well organized and gives a good amount of extra resources to read on but, I think it can become better if, the instructor did not rush through some of the subjects and spent more time explaining (especially towards the end of the course). The discussion forums help in these types of situations but, there will be a lot of searching dedicated to the specifics you are looking for. Overall an update to the course based on feedback of people that completed the course (from discussion forums) seems necessary. Adding an extra 5-10 minutes to some of the video contents can save the student from hours of research on the internet and confusion (sometimes due to the outside source). I'm not saying one should not spend time learning the material further from outside sources. Just saying the explanation might help avoid the confusion caused by looking into other sources.