返回到 Bayesian Statistics: From Concept to Data Analysis

4.6

星

2,491 个评分

•

657 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 Eben E

•Apr 12, 2020

This was a were educational course. I had trouble understanding R programming but with this topic, most of the programs became more clear to me.

创建者 Cooper O

•Jun 28, 2017

A Fantastic course. Detailed learning materials, Lots of opportunities to test your knowledge, and difficult enough to make you learn something!

创建者 Nitin K

•Jun 01, 2017

I loved everything about this course. It reminded me of my time in school. Papers and pencils. I look forward to attending the follow up course.

创建者 Tiannan S

•Jul 06, 2020

As a computer science student, I feel Bayesian approach is much more intuitive and more computationally friendly than the frequentist paradigm.

创建者 Fernando D L

•Mar 11, 2019

It's a good course to know the principal concepts of Bayesian statistics. Also, the course has excellent examples to understand thew concepts.

创建者 Orfeas K

•Mar 02, 2018

I really appreciated the content, and the way it was taught by Prof. Lee. His explanations were intuitive, without loss of mathematical rigour.

创建者 Giovanni G

•Jul 30, 2020

Consistent and mathematically dense. If you want to go through every passage this course gives you solid understanding of Bayesian statistics.

创建者 RIcardo G M

•Dec 15, 2019

Very good course. Concepts are very well explained, and quizzes are really helpful to apply and further

understand the explanations provided.

创建者 Kuntal B

•Nov 13, 2019

Thanks, Coursera. This is a good course. It would be helpful if we get any proper class notes on Jeffrey's prior and Multivariate regression.

创建者 Artem B

•Jul 03, 2019

Great course with a lot of simple, but illustrative exercises. It may be useful to have some basic prior knowledge of econometrics/statistics

创建者 Michael W

•Jan 16, 2019

Great introductory course. It was challenging but doable for someone who has not take college level mathematics or statistics in a few years.

创建者 Robert K M

•Feb 12, 2018

Invaluable. Excellent quizzes. A few terms could have been better defined, and a few more examples wouldn't hurt, but overall excellent.

创建者 Damian C

•Nov 10, 2016

Very well presented course. Interesting and intuitive introduction into the fascinating Bayesian world.

Many thanks and congratulations!!!

创建者 Ariel A

•Oct 12, 2017

Great course, it has the right proportion of theory and practice. It's a great start for anyone who wants to dive into Bayesian Analysis.

创建者 Hari S

•Feb 05, 2020

Thought is a simple manner. Made complex concepts look very easy. Would surely recommend this course. Thanks Prof. Herbert Lee and team.

创建者 Vignesh R

•Oct 08, 2018

Awesome course that helped me overcome the Bayesian statistics way of thinking hurdle. Now, I want to go on and learn MCMC, Metropolis !

创建者 Qinyu X

•Feb 02, 2020

The course is generally great. Nonetheless, it is not recommended for those without a statistical background and knowledge of calculus.

创建者 Naseera M

•Feb 12, 2017

Very good course. Prof. Lee explains each concept well. Bayesian Stats makes more sense to me now than before!!

Thanks so much Prof. Lee

创建者 Gustavo C

•Oct 04, 2018

I loved this course, I learned a lot and I hope I will be able to use this knowledge when I go back to college for my Master's degree.

创建者 Evgenii L

•May 02, 2018

A very good course. Even better if you continue with the 2nd course that teaches about how to implement Bayesian data analysis in JAGS

创建者 Joseph G

•Dec 18, 2016

I enjoyed the lecturer, the material is relevant, and the tests are well tailored to ensure you are absorbing the correct information.

创建者 Rodrigo G

•Jan 16, 2020

Give you great insight. Very intuitive. Although we went through the last week rather quick (more explanation would have been better)

创建者 Jenna K

•May 13, 2019

The lectures are at the right pace; concise and challenging. Great examples. Thank you so much for providing us with great materials.

创建者 Matthew S

•Apr 05, 2020

Pretty challenging course. Well organized and well delivered. I learned from the exercises and also the feedback from the exercises.

创建者 Dr. R M

•Nov 15, 2017

Very informative and clear presentation of the material, which makes it fun and quick to learn the topics. Very good quiz questions.

- 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