Conditional probability and conditional expectation; Stochastic modeling; discrete time Markov chains including classification of states, stationary and limiting distributions; exponential distribution and the Poisson processes; queueing models; applications to computer systems, operations research and social sciences. Prerequisite(s): STAT 2655 with a grade of C- or higher; or permission of the School. Lectures three hours a week, tutorial one hour a week. [0.5 credits]
Conditional probability and conditional expectation; Stochastic modeling; discrete time Markov chains including classification of states, stationary and limiting distributions; exponential distribution and the Poisson processes; queueing models; applications to computer systems, operations research and social sciences. Prerequisite(s): STAT 2655 with a grade of C- or higher; or permission of the School. Lectures three hours a week, tutorial one hour a week. [0.5 credits]
