Markov Chains: Absorbing Classes

This lecture covers Markov chains with absorbing classes, focusing on exercises related to applied probability and stochastic processes. The slides present exercises on finding open and closed classes in a transition probability matrix, calculating expected values, and analyzing the behavior of a frog hopping on lily pads. The instructor discusses the graphical representation of Markov chains, cubing transition matrices, and solving the gambler's ruin problem. Through practical examples, students learn to determine probabilities of staying in a state, reaching a specific state, and the average time to reach a destination.