Probability space, conditional probability, Bayes theorem. Combinatorial analysis. Random variables (r.v.'s), distribution and density functions. Expected value, moments, characteristic function. Function of r.v.'s, Multiple r.v.'s, conditional distributions, independent r.v.'s. Multivariate Gaussian r.v.'s. Parameter estimation, confidence intervals, hypothesis testing. Introduction to random processes: mean, autocorrelation, power spectral density. Prerequisite: E&C-ENG 313.
Introduction to Probability and Random Processes
Electrical and Computer Engineering
Monday, March 13, 2017 to Friday, May 26, 2017