Decision Analysis Under Uncertainty

The course goal is to understand, model and improve decision making under uncertainty and complexity. Bayesian principles and expected utility theory are combined, their underlying assumptions critically reviewed, and alternative theories surveyed. Other issues addressed include decision with multiple attributes. Priority may be given to Management Sciences students.