This course is a PREREQUISITE for theoretical statistics courses and further courses in probability and stochastic processes. Basic probability theory: probability models; discrete and continuous random variables; moments; jointly distributed random variables; transformations and generating functions. Inequalities and limit laws. Distributions include: binomial, Poisson, exponential, gamma, normal. Applications include: elementary stochastic processes, time-to-failure models, binary communication channels with Gaussian noise. (42/0/0/0/0) COREQUISITE:
