Statistics and Decision Analysis

3 credits · Graduate

Course coverage includes foundations, probability modelling for inference and prediction, utility/loss function development, numerical methods for evaluating decisions, examples in business, finance, economics, medical decision making, and other areas. The course treats statistical model parameter estimation and testing as decision problems, statistical design as decision analysis, links of probabilistic forecasting and decision analysis, Bayesian analysis in decision problems, theory and numerical algorithms for optimisation, and examples in application of decision analysis to real-world problems. Prerequisite: MATH 218 (or equivalent), STA 360/601, and STA 532 (or 732).