I teach MBA-level courses in probability and statistics, and PhD-level courses in static optimization and dynamic optimization.
Statistical Methods for Managers (DECS 433):
The goal of DECS-434 is to teach students to solve real problems using regression analysis and related statistical techniques for quantitative analysis of data. Students will be able to adapt models and interpretations to such difficulties as omitted variable bias, multicollinearity, and heteroskedasticity. The statistical principles underlying regression will be illustrated via a number of applications in areas such as finance, marketing and management.
Turbo Decision Making and Statistics (DECS 445)
This accelerated course combines the core curricula in statistics (see above) and decision-making for managers. The decision-science portion of the course includes such topics as expected utility, risk aversion, value of information, option value, information aggregation, and herding.
Foundations of Managerial Economics I: Static Decision Models (MECS-460-1)
This course provides essential tools for those planning to create or apply economic theory. The course can be divided very broadly into optimization, fixed-point theory, and introduction to probability theory. More specifically, we will cover: linear programming, Kuhn-Tucker conditions, Brouwer and Kakutani fixed-point theorems, supermodularity, and basics of probability and Lebesgue measure while illustrating uses in finance, game theory, general equilibrium, and matching.
Foundations of Managerial Economics II: Dynamic Decision Models (MECS-460-2)
This course provides a rigorous introduction to dynamic optimization techniques used in discrete and continuous time stochastic optimization problems. Topics covered in the course include discrete time discounted dynamic programming, stochastic zero sum games, envelope theorems, multi-armed bandit problems, negative dynamic programming, optimal stopping, positive dynamic programming, optimal gambling strategies, bold and timid play, as well as, continuous time calculus of variations and optimal control.