Advanced Probability: SummaryCovers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.
Stochastic Models for CommunicationsCovers random vectors, joint probability density, independent random variables, functions of two random variables, and Gaussian random variables.
Continuous Random VariablesExplores continuous random variables, density functions, joint variables, independence, and conditional densities.
Linearity of ExpectationCovers Linearity of Expectation, Markov's inequality, random variables, and transitive tournaments.