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.
About this Course
Skills you will gain
- 5 stars66.88%
- 4 stars25.49%
- 3 stars5.33%
- 2 stars1.32%
- 1 star0.96%
TOP REVIEWS FROM BAYESIAN STATISTICS: FROM CONCEPT TO DATA ANALYSIS
This was an invaluable learning experience. I was delighted to go through this learning.
I strongly suggest this course to anyone who wants to learn or refresh their statistics knowledge.
This is a good course for reviewing basic concepts of statistics, and good for starting learning Bayesian, as introduced as a basic course. If you want to learn deeper, go and find another course!
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.
Great course in a difficult subject. Well structured. Requires some previous knowledge otherwise difficult to follow. Big thanks to professor Lee for bringing to us this content.
About the Bayesian Statistics Specialization
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