返回到 Bayesian Statistics: From Concept to Data Analysis

星

2,683 个评分

•

700 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

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

筛选依据：

创建者 Hari S

•Feb 5, 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 8, 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 2, 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 4, 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 2, 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 5, 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.

创建者 Xiaoyang G

•Jul 7, 2016

This course is a very good introductory of bayesian statistics. But it better that you have known the basic statistics inference.

创建者 Humberto R C

•Nov 6, 2017

A clear and compact introduction. Quizzes and exercises are relevant. I got acces to grades and feedback in the audit one I took.

创建者 Raj s

•Feb 8, 2017

Learned something new :). Lecture were excellent, but, I need time to digest and hope I will get opportunity to use it in future.

创建者 Tetsuhiko O

•Jan 20, 2018

I studied basic theory from these lectures. I will try again and again until I understand Baysian Statistics concept completely.

创建者 Felipe C

•Dec 13, 2020

Quite interesting course ant not too long. I learnt many interesting and useful concepts in statistics. Highly recommendable.

创建者 Jose M R F

•Jul 14, 2019

Very well explained. Lectures are given in a very nice way as the professor writes. Exercises and quizzes are very well done.

创建者 Zhirui W

•Sep 26, 2017

Become very clear about all the formula and derivation of Bayesian Statistics after taking this course. Strongly recommended.

创建者 Eduardo M

•Jan 4, 2019

Very good material! The Prof explains very easily the contents of the course. Great course! I recommend. E. Martins, Brazil

创建者 Leon W

•Aug 5, 2018

The video content is not too much. However, students can learn and practise a lot from supplementary materials and quizzes.

创建者 Salaheldin G

•Dec 26, 2017

Very useful crash course in Bayesian Statistics. It requires some basic knowledge in statistics and probability as stated.

创建者 Miles D R

•Aug 15, 2019

This course was dense, concise, and yet easy to follow for individuals that are fairly comfortable with basic statistics.

创建者 Francisco J S G

•Aug 26, 2018

A really hard course but useful for those who want to know more about statistics and how it is related to Bayes' theorem.

创建者 Álvaro C Q A

•Mar 27, 2018

It's a good introductory course to Bayesian statistics, a second part with Gibbs Sampling, Markov and MCMC would be nice.

创建者 Jack

•May 17, 2018

The teacher is excellent and charming and the course is also easy to follow. However, with more exercise will be better!

- 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

- 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