Fall
MGTECON 640: Quantitative Methods for Empirical Research
This is an advanced course on quantitative methods for empirical research. Students are expected to have taken a course in linear models before. In this course I will discuss modern econometric methods for nonlinear models, including maximum likelihood and generalized method of moments. The emphasis will be on how these methods are used in sophisticated empirical work in social sciences. Special topics include discrete choice models and methods for estimating treatment effects.See schedule
Spring
MGTECON 535: Statistics and Causality
Most statistical questions involving data ultimately are about causal effects. What is the effect of changing prices on demand? What is the effect of an advertising campaign on demand. In this course we discuss statistical methods for analyzing causal effects. We look at the analysis and design of randomized experiments. We also look at various methods that have been used to establish causal effects in observational studies. Students will develop the skills to assess causal claims and learn to ask the right questions and evaluate statistical analyses. You will carry out research projects and work with statistical software.See schedule
Winter
OIT 536: Data for Action: From Insights to Applications
Data for Action is an MBA compressed course dedicated to identifying value in and creating value from data. It deals with the technical, legal, regulatory and business strategic decisions that must be considered when delivering solutions to customers.See schedule