Love’s Labor Won

Description

Basic concepts such as random experiments, probability axioms, conditional probability, and counting methods
Single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, characteristic functions, random vectors, and inequalities
Limit theorems and convergence
Introduction to Bayesian and classical statistics
Random processes including processing of random signals, Poisson processes, discrete-time and continuous-time Markov chains, and Brownian motion
Simulation using MATLAB, R, and Python (online chapters)