Introduction to probability theory and its applications in engineering science: basic concepts of probability, counting, conditional probability, Bayes' rule, independence; probability models; random variables, distribution functions, probability mass functions, probability density functions; expectation, variance, moments; jointly distributed random variables; transformations of random variables. Distributions: Bernoulli, binomial, geometric, negative binomial, Poisson, uniform, exponential, normal. Applications: elementary stochastic processes, noisy communication channels.
(Lec: 3, Lab: 0, Tut: 0.5)