DF
5.0Reviewed Mar 30, 2023
Amazing and capable professor, extremely interesting topic. I absolutely loved the fact that the coding was taught in both R and Excel and that the code was also available for the student.
Bayesian Statistics: From Concept to Data Analysis
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.
Status: Statistical Modeling
Status: Statistical Software
IntermediateCourse11 hours
Featured reviews
FL
5.0Reviewed Oct 29, 2016
Amazing course ! Excellent. Prof. Herbert has a great didactics, the material is clear and very well planned, including the assessments. Thank you very much. Flavio Lichtenstein (Brazil).
RK
4.0Reviewed Oct 16, 2024
The concepts could have been made much more easier, simpler and more examples could have been inculcated. But overall, a great course to gain in-depth insights for a starter on Bayesian Statistics
DG
4.0Reviewed Dec 8, 2019
It was a good course for me to get familiar with the new perspective on statistics. Thank you! Maybe, some extended practice exercise at the end of the course would make it even better)
MS
4.0Reviewed Oct 9, 2018
Good use of R but maybe use the actual coefficient from the equations themselves rather than picking numbers pre-selected which may confuse.Unable to look at discussion forum without posting myself.
AO
5.0Reviewed Jul 20, 2020
Prof. Lee's approach is simple and intuitive. There are exercises throughout the videos, which help you make sure you and the professor are on the same track. I would certainly recommend it!
JH
5.0Reviewed Jun 26, 2018
Great course. The content moves at a nice pace and the videos are really good to follow. The Quizzes are also set at a good level. You can't pass this course unless you have understood the material.
KK
5.0Reviewed Nov 13, 2020
A very good introduction to Bayesian Statistics.Couple of optional R modules of data analysis could have been introduced . However, prerequisites are essential in order to appreciate the course.
AS
5.0Reviewed Jul 13, 2020
It's an amazing course, I strongly recommend. It was like a complementary course for the Data Analysis course of my university, giving a wide explanation over bayesian analysis. I'm glad to finish it.
SP
5.0Reviewed Nov 15, 2017
This is first time exposure to bayesian statistics and I must say it has given me a different perspective to analyzing data especially when dealing with unpredictable data or unknown data.
GG
4.0Reviewed Nov 25, 2016
A good course but neither notes nor lectures were not in much details. But still it was worth my time. I strongly recommend it if you want a subtle introduction to Bayesian Statistics.
MD
4.0Reviewed Feb 18, 2020
the notes for the lectures are missing.In my opinion the notes, which includes the video materials could be very useful.the course was good. I learnt some new concepts in bayesian thinking.