Bayes Rules! by
Discussing everything from chocolate milk to dating apps, and referencing shows like “Parks and Recreation” and “RuPaul’s Drag Race,” an open access book co-authored by Mine Dogucu removes barriers to learning Bayesian statistics and finds new ways to engage readers.
Journals
eBooks
Bayesian Statistics for the Social Sciences by 
Statistical Modeling with R by 
Statistical Rethinking: A Bayesian course with examples in R and Stan by Videos / Lectures
Open Access Resources
About this course:
Duke students may take this class through Coursera for Duke. It 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."
