Course Schedule and Catalog

Long Title: HIERARCHICAL BAYES MODELS IN MARKETING

Department: Business

Grade Mode: Standard Letter

Course Type: Lecture

Credit Hours: 3

Description: The course aims to develop an understanding of Bayesian inference, with a special focus on empirical applications in marketing. The course starts with a brief theoretical foundation to Bayesian inference and subsequently focuses on empirical methods. Topics include Bayesian linear regression, multivariate regression, importance sampling and its applications. The course focuses on Markov Chain Monte Carlo (MCMC) methods including the Gibbs Sampler and the Metropolis-Hastings algorithm and their applications. The course also introduces the notion of Data Augmentation and its application to estimate truncated models (univariate Tobit and multivariate Tobit models). The overall focus of the course is on applying these methods for empirical research using a programming language such as R. Repeatable for Credit.