IE 255 Probability for Industrial Engineers

Credit Information: 
(3+0+0) 3
Description: 
Basic topics in probability theory; sample space, probability, and conditional probability; random variables, marginal, joint and conditional distributions; expectations and conditional expectations; hypergeometric, binomial, geometric distributions and their implications in IE/OR; Poisson, exponential, Erlang, gamma distributions and the Poisson arrival model; moment generating functions and Laplace transforms; law of large numbers, central limit theorem, and the Normal distribution; numerical and computational aspects of random variable generation.