返回到 Bayesian Statistics: From Concept to Data Analysis

4.6

星

2,504 个评分

•

658 条评论

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....

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.

JB

Oct 17, 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

筛选依据：

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 Xu Z

•Apr 07, 2017

Very concise and easy to follow to the end. The linear regression part could be more clear (i.e., with a lecture on the background).

创建者 Alex C

•Feb 17, 2020

The last section, normal data, which is very important, could have been instructed in a slower, less hasty way with more details.

创建者 Björn A

•Jun 21, 2020

Great course to get acquainted with Bayesian statistics and inference. Just wished seeing a bit more of mathematical background.

创建者 Devid

•Nov 28, 2018

Need more information about linear regression, given material is not enough to understand topic and effectively find solution.

创建者 Ethan V

•Nov 02, 2017

A bit dry overall, but I appreciate the rigor and precision, along with the practical examples in R. I learned a great deal.

创建者 Sameer G

•Nov 04, 2017

Hi , this course opened a door for me in Data analysis. Very intuitive & must course for any person exploring data science.

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 abhisingh03

•Jan 15, 2017

This course has given me some good new insights into perceiving data and has got me started nicely I am very great full.

创建者 Jakob L

•Mar 16, 2019

Good introduction and interesting topics. However, some of the model analyses are not appropriate and feels artificial.

创建者 Rohit J V

•Feb 04, 2018

As a graduate student pursuing Machine Learning, this was a great course for me to get introduced to Bayesian Models.

创建者 Muksitul I

•Jul 02, 2018

Well explained and articulated. You can apply it straight to your work problems. I really enjoyed doing the course.

创建者 Sankar M

•Jun 21, 2020

Excellent introductory course. Some of the concepts in the later part of the course are not explained well though.

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 lai p w

•Jan 01, 2018

I can learn the concept, but need to understand the details well in other ways. eg. reading, or searching online

创建者 jose a z r

•Aug 28, 2017

Very helpfull course. I will use the principles taugh for other topics like machine learning. Thans for sharing.

创建者 Jan B

•Oct 03, 2020

Great course with a good theory/practice balance, but examples could be a bit more refreshing and less boring.

创建者 Pranesh K

•Mar 10, 2017

The course is excellent to learn all the basic stuff needed to master the technique of Bayesian Data Analysis.

创建者 Guruprasad K

•Jun 25, 2020

More assignments and live and truncky examples applying the principles would make course even more wonderful

创建者 Somnath C

•Dec 03, 2016

I wish the last week were more explanatory. Although overall now I do have an idea. It's a good course. :-)

创建者 Sarah D

•Aug 04, 2020

Could do with more exercises.

However, I found some elsewhere on the internet, so that was complementary

创建者 Marco

•Jul 30, 2020

Pretty good introductory material overall. Only disappointing part was the section on linear regression.

创建者 Sergio

•Sep 30, 2018

Very nice introductory course, practical and to the point. Good starting point for more detailed courses

创建者 Mangmang Z

•Jan 11, 2018

A little hurry in the normal distribution part, otherwise a great course for Bayesian introduction.

创建者 Guangyuan L

•Mar 07, 2019

a little bit difficult, I think you need to hold a solide background toward inferential statistics

- Finding Purpose & Meaning in Life
- Understanding Medical Research
- Japanese for Beginners
- Introduction to Cloud Computing
- Foundations of Mindfulness
- Fundamentals of Finance
- 机器学习
- 使用 SAS Viya 进行机器学习
- 幸福科学
- Covid-19 Contact Tracing
- 适用于所有人的人工智能课程
- 金融市场
- 心理学导论
- Getting Started with AWS
- International Marketing
- C++
- Predictive Analytics & Data Mining
- UCSD Learning How to Learn
- Michigan Programming for Everybody
- JHU R Programming
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- AI for Medicine
- Good with Words: Writing & Editing
- Infections Disease Modeling
- The Pronounciation of American English
- Software Testing Automation
- 深度学习
- 零基础 Python 入门
- 数据科学
- 商务基础
- Excel 办公技能
- Data Science with Python
- Finance for Everyone
- Communication Skills for Engineers
- Sales Training
- 职业品牌管理职业生涯品牌管理
- Wharton Business Analytics
- Penn Positive Psychology
- Washington Machine Learning
- CalArts Graphic Design

- 专业证书
- MasterTrack 证书
- Google IT 支持
- IBM 数据科学
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI Applied Project Management
- Instructional Design Certificate
- Construction Engineering and Management Certificate
- Big Data Certificate
- Machine Learning for Analytics Certificate
- Innovation Management & Entrepreneurship Certificate
- Sustainabaility and Development Certificate
- Social Work Certificate
- AI and Machine Learning Certificate
- Spatial Data Analysis and Visualization Certificate

- Computer Science Degrees
- Business Degrees
- 公共卫生学位
- Data Science Degrees
- 学士学位
- 计算机科学学士
- MS Electrical Engineering
- Bachelor Completion Degree
- MS Management
- MS Computer Science
- MPH
- Accounting Master's Degree
- MCIT
- MBA Online
- 数据科学应用硕士
- Global MBA
- Master's of Innovation & Entrepreneurship
- MCS Data Science
- Master's in Computer Science
- 公共健康硕士