Description:

In this tutorial, we will walk through the basics of STAN- an open-source software for Bayesian inference. We will build a simple linear regression model in STAN and lightly discuss the advantages of using a Bayesian framework. We will be using STAN with Python, but STAN allows interfacing with R, MATLAB, Julia, Stata, and more.

Prerequisites: Participants should be familiar with Python at the level of the Python Fundamentals Bootcamp, another introductory Python workshop, or be a self-taught Python coder. Basic familiarity with regression analysis is required.