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Week Ten – Elements of probability and statistics (events, sample space, random variables), probability distribution functions, conditional probabilities Review of probability and statistics Context: Probability theory underlies the study of stochastic processes, the general subject matter to be covered in the remainder of the course. We review the basic elements of probability highlighting conditional probabilities, and discuss two important distributions: the exponential and Poisson. Purpose: To provide you with a refresher on probability theory, including the sample space, events, random variables, probability distributions, and the laws of conditional probability. Several examples are given to illustrate concepts. Objectives: At the end of this lesson, you will be able to: 1. Define the sample space of an experiment and relate the set of outcomes to the random variables of interest. 2. Work with conditional probabilities and Bayes’ theorem. 3. Compute various probabilities associated with simple experiments such as rolling dice and flipping coins. 4. Explain the memoryless property of the exponential distribution and compute various probabilities of events governed by the exponential. 5. Explain the relationship between the exponential distribution and the Poisson distribution. 6. Work with the Poisson to compute various probabilities.