This is a graduate level course for students interested inManagement Science, Operations Research, Finance, Economics, and MathematicalFinance. The course objective is to familiarize students with classicaltheories on decision making in a stochastic environment and apply data to putthose theories into practice. This course will improve student’s understandingof the theory of decision making under uncertainty by rigorously proving someof the classical results which at the undergraduate level are often just statedas a fact. Students will also gain exposure to classical and recentdevelopments in the literature, strengthen their literature review abilities,enhance their presentation skills, and teach them how to put theory intopractice by applying models of decision making to real-world data. This course isstructured into three parts in order to achieve the goals stated above. In thefirst part of this course, we will teach the classical theories on decisionmaking in a stochastic environment and introduce several empirical puzzles andparadoxes in the classic lecture format. In the second part of the course,students will read and present research papers on the most importantalternative theories of decision making under uncertainty and recent advances.Finally, students will learn how to present and defend their own researchproject, and to discuss the findings of their peers.