Back to Bayesian Statistics: From Concept to Data Analysis

4.6

stars

2,539 ratings

•

667 reviews

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

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By 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.

By 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.

By 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.

By 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.

By 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.

By 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.

By 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.

By 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.

By Zhirui W

•Sep 26, 2017

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

By 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

By 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.

By Salaheldin G

•Dec 26, 2017

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

By 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.

By 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.

By 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.

By 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!

By Georgios P

•Feb 24, 2017

Very good introduction to baysian concepts and very helpful in understanding the difference with frequentist statistics.

By Shakir B

•Aug 3, 2020

Initially I was a bit put off. But what a compilation of well thought set of lectures and quizzes! Thoroughly enjoyed.

By Бызов А

•May 27, 2018

Marvellous course! Thank you very much! I would really appreciate, if you'll create an advanced version of this course

By Flavio P

•Aug 10, 2017

Very interesting. It can help taking notes during the course... to avoid going again through it and take them ex-post.

By kacl780tr

•Jul 6, 2017

Excellent course, although it would have been nice to get more content on uninformative priors and Fisher information.

By 张宁

•Sep 24, 2016

This course are excellent and Thanks for Prof for offering the course. I've learned a lot from the course. Thank you.

By 郭冰

•Mar 10, 2017

I have learned a lot from this course. As there is not course like this one in my univeristy, I really appreiate it.

By Zach K

•Aug 3, 2020

I learned a ton about statistics and probability distributions. It was great prep for my machine learning classes.

By Xilu W

•Nov 19, 2016

I'm a graduate student in mechanical engineering. Thanks for the open course, it is really convenient and helpful!

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