EE 315 · Probabilistic Methods in Electrical Engineering

This course covers the fundamentals of probability theory, including single and multiple discrete and continuous random variables, probability density functions, and Gaussian and other distributions. It covers joint and conditional probabilities, moments, statistical averages, and the central limit theorem, before introducing random processes, including stationarity, ergodicity, correlation functions, and power spectral density. The course concludes with the response of linear systems to random signals and a brief introduction to statistics, covering point and interval estimation and hypothesis testing.