Introduction to Statistical Decision Analysis

Quantitative methods for decision making under uncertainty. Probability theory, personal probabilities and utilities, decision trees, ROC curves, sensitivity analysis, dominant strategies, Bayesian networks and influence diagrams, Markov models and time discounting, cost-effectiveness analysis, multi-agent decision making, game theory. Prerequisite: Statistical Science 230, 231, or 240L.