Name: Bayesian Statistics
Brand: Duke University
Availability: OnlineOnly
Rating: 3.8 (255 reviews)

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Learner Reviews & Feedback for Bayesian Statistics by Duke University

3.8

stars

798 ratings

About the Course

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution. Additionally, the course will introduce credible regions, Bayesian comparisons of means and proportions, Bayesian regression and inference using multiple models, and discussion of Bayesian prediction. We assume learners in this course have background knowledge equivalent to what is covered in the earlier three courses in this specialization: "Introduction to Probability and Data," "Inferential Statistics," and "Linear Regression and Modeling."...

Top reviews

Aug 24, 2017

An interesting and challenging course, would be better with more real examples and explanation as some of the material felt rushed

Jul 28, 2016

The section about Beta-Binomial Conjugate is taught very fast and unless the student is quite familiar with Beta and Gamma distributions, it makes it very difficult to follow the course.

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