Poisson Process: Properties | EPFL Graph Search

Explores simulation pitfalls, random numbers, discrete & continuous distributions, and Monte-Carlo integration.

Explains the importance of moments in measuring distribution properties, such as expectation and variance.

Covers the properties of the symmetric random walk in stochastic processes.

Covers the Poisson process, a stochastic model for communications, focusing on the probability law.

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.