| Abstract: A Markov chain describes how a process moves from state to state over time. Real world applications can be found in many fields including biology, physics, economics, sociology and games of chance. The structure of a Markov chain is best represented by a matrix of transition probabilities. A variety of examples will serve to illustrate the basic properties of the chains and the usefulness of the transition matrices. Real world examples will include applications of Markov chains to gambling, the game of tennis, and an original example about two-person random walks. |
Presenting at HRUMC:
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