Bayesian Statistics: From Concept to Data Analysis
Learn the Bayesian approach to statistics in this comprehensive course. Understand probability, data analysis, and the philosophy behind Bayesian methods. Compare it to the Frequentist approach and discover the benefits. Gain a better understanding of uncertainty, intuitive results, and explicit assumptions. This active learning experience combines lectures, demonstrations, readings, exercises, and discussions. Choose between Microsoft Excel or R for computing. Develop your mathematical skills and interpretation abilities. Complete this course to master Bayesian concepts, differentiate from Frequentist methods, and perform basic data analyses.
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.
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