This course introduces the fundamentals of probability theory in the context of models for decision making under uncertainty. Basic concepts of probability theory are introduced including mean, variance, joint and conditional probabilities and Bayes Theorem. Discrete and continuous random variables are introduced with a special emphasis on binomial, Poisson, exponential and normal distributions and the Central Limit Theorem. Decision-making techniques such as decision trees, simulation and queueing models are interleaved in the course as applications of the aforementioned concepts. These techniques are illustrated using examples drawn primarily from the business world such as risk analysis, option pricing and yield management.