This course covers analysis of problems and decisions under risk and uncertainty. Review of probability, statistics and Bayes’ theorem. Decision trees, decision theory, utility theory, value of information, simulation and risk analysis. Process simulation with a graphical interactive software package. Programming and development of basic simulation models. Discussion of model validation and variance reduction techniques. Quantification and measurement of risk and its measures such as standard deviation and conditional value at risk (CVar).