In part two of this two-part series, we dive deeper into statistical modeling from a Bayesian perspective. Once again we present the concepts by way of comparing them to traditional (Frequentist) modeling approaches. For example, what is the Bayesian approach for analyzing data that would normally call for logistic regression? How would the implementation and interpretation differ? We’ll also cover the basics of model checking and visualization. This workshop is intended for all audiences, but we highly recommend attending Part 1.