返回到 Bayesian Statistics: From Concept to Data Analysis

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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 Brian K

•Feb 19, 2019

Great introduction to Bayesian statistics. Very helpful for me, especially for understanding some of the times when priors might be useful, and how they can aid me.

创建者 Frank K

•Jul 1, 2017

Taking this course hase been fun. The material is presented in a clear and structured way, the Tests help to understand and deepen the knowledge. I can recommend it.

创建者 Sankarshan M

•Aug 27, 2017

very good course with good concept and work. Content is very rich. Assignments are very good. It was very helpful for me. Thanks for providing such a good course.

创建者 Neal S

•Apr 10, 2020

Overall a great course! The honors assignments helped deepen the understanding of the concepts, and weren't just extra work.

The instruction videos are a bit dry.

创建者 ENRICO S

•Aug 17, 2017

Great course. I was more confident in frequentist than Bayesian one so, I found this course very enlightening for me and topics' structure has never been boring.

创建者 Patricia B

•Aug 1, 2017

Necessary concepts are reviewed to the necessary depth. This is a rigorous yet light material that presents statistics on university intermediate/advanced level.

创建者 Luca M

•May 16, 2017

A concise and clear introduction to the Bayesian paradigm. Its conciseness make it suitable for frequentists wanting to get a quick overview of the Bayesian Way.

创建者 BÙI T H

•Dec 2, 2017

Thank you so much, Herbert Lee. I really like the way you explain everything clearly and how you organizes the contents. I recommend this course for my friends.

创建者 Elma J

•May 11, 2020

excellent course to understand Bayesian approach. i have good idea bout prior and posterior probability, predictive distribution , maximum likelihood estimates

创建者 Raj K

•Dec 29, 2019

The awesome course really liked the mathematically. If someone really want to understand the Bayesian statistics, they should definitely go through this once.

创建者 Fabian S

•Jan 18, 2018

A great introduction to Bayesian Statistics for everyone who has some basic knowledge of calculus and is familiar with the fundamentals of probability theory.

创建者 Antoine N

•Aug 21, 2017

Great introduction to the Bayesian framework! The exercises are relevant and I look forward to the second part (Bayesian Statistics: Techniques and Models).

创建者 Isaac D

•Jan 20, 2017

A step by step course, designed to pay attention all the time with tons of practical examples and very clear explanations, I would definitely recommend it!!

创建者 jl b

•Jun 11, 2020

Herbert is clear, gives great examples, and is easy to follow. The question prompts are helpful, and the quizzes thoughtful and challenging. Great course.

创建者 Naveen M N S

•Sep 21, 2017

Very good course for fundamentals of Bayesian statistics. Made me understand Monte Hall problem, conditional probability, etc. in a totally different way.

创建者 Pawel R

•Oct 3, 2016

The course creates great foundations for digging deeper into more complex concepts and trying to run some Bayesian statistics on simple real life problems

创建者 me m

•Dec 1, 2019

A mathematics course I really enjoyed because the instructor was actually teaching the material as best as one could without meeting the students. Great.

创建者 Laure N

•Mar 6, 2018

Thank you very much for sharing your knowledge with the public. Now I am no more afraid to face the book 'Bayesian Data Analysis' by A. Gelman et al.

创建者 Allan V d C Q

•May 7, 2020

I really enjoyed this course. Dr. Lee is a really good instructor. The materials and tests are good as well and will help you during the journey.

创建者 Thadeu F

•Jul 5, 2017

Great course. Intermediate to advanced level (at least for me). You must have good foundation in probability. If so, you will learn a lot. Thanks

创建者 Simiao R

•Jul 20, 2020

Good course about bayesian! I finally understand the relationship between frequentist idea and Bayesian approach and Beta gamma distributions

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 27, 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 1, 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 6, 2020

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