DSCI 6653 - Bayesian Data Analysis

Prerequisite: DSCI 6602. Bayesian data analysis is an approach to statistical modeling and machine learning that is becoming more and more popular. It provides a uniform framework to build problem specific models that can be used both for statistical inference and for prediction. 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 will introduce students to Bayesian data analysis, starting with the concept of probability and moving to the analysis of data. In particular, this course will discuss the philosophy of the Bayesian approach as well as implementation for common types of data, compare the Bayesian approach to the more commonly-taught Frequentist approach, and present some of the benefits of the Bayesian approach. 3 credits.