Stochastic Processes, Discrete Markov Chains
http://www.maa.org/taxonomy/term/40519/0
enTennis with Markov
http://www.maa.org/programs/faculty-and-departments/classroom-capsules-and-notes/tennis-with-markov
<div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>In the game of tennis, if the probability that player \(A\) wins a point against player \(B\) is a constant value \(p\), then the probability that \(A\) will win a game from deuce is \(p^2/(1 - 2p + 2p^2)\). This result has been obtained in a variety of ways, and the authors use a formal Markov chain approach to derive it.</p>
</div></div></div>Computing the Fundamental Matrix for a Reducible Markov Chain
http://www.maa.org/programs/faculty-and-departments/classroom-capsules-and-notes/computing-the-fundamental-matrix-for-a-reducible-markov-chain
<div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p><em>A Markov chain with 9 states is used to illustrate a technique for finding the fundamental matrix.</em></p>
</div></div></div>Euler Convergence: Probabilistic Considerations
http://www.maa.org/programs/faculty-and-departments/classroom-capsules-and-notes/euler-convergence-probabilistic-considerations
<div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p><em>The authors show, using probabilistic methods, that convergence implies Euler convergence, but not conversely.</em></p>
</div></div></div>The Gunfight at the OK Corral
http://www.maa.org/programs/faculty-and-departments/classroom-capsules-and-notes/the-gunfight-at-the-ok-corral
<div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p><em>This article uses a generalization of a three-way gunfight to motivate the construction and solution to a first order linear system of difference equations. The method of undetermined coefficients is used to develop a general solution to the dynamical system. Probabilities of the system converging to each final (absorbing) state are found. According to the author, many mathematical models can be approached from the point of view of discrete dynamical systems.</em></p>
</div></div></div>Stochastic processes, discrete Markov chains (Classroom Capsules and Notes)
http://www.maa.org/programs/faculty-and-departments/course-communities/stochastic-processes-discrete-markov-chains-classroom-capsules-and-notes
The Ehrenfest Chains
http://www.maa.org/programs/faculty-and-departments/course-communities/the-ehrenfest-chains
Markov Chains
http://www.maa.org/programs/faculty-and-departments/course-communities/markov-chains
A Random Walk in One Dimension: Applet Demonstration
http://www.maa.org/programs/faculty-and-departments/course-communities/a-random-walk-in-one-dimension-applet-demonstration
Discrete - Time Markov Chains
http://www.maa.org/programs/faculty-and-departments/course-communities/discrete-time-markov-chains
Gambler's Ruin - Expository Introduction with diagrams
http://www.maa.org/programs/faculty-and-departments/course-communities/gamblers-ruin-expository-introduction-with-diagrams
Gambler's Ruin - Expository Introduction
http://www.maa.org/programs/faculty-and-departments/course-communities/gamblers-ruin-expository-introduction