Markov Chains - Math Modelling | Lecture 27

For the final lecture of this series on mathematical modelling we will discuss Markov chains. We will see that Markov chains are a type of discrete-time stochastic model that lies at the intersection of dynamical systems and probability models. Much of the basics are introduced with a simple Markov chain model while the second half of the lecture is dedicated to working through a more complex example that combines Markov chains with customer arrivals based on the Poisson distribution.

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This course is taught by Jason Bramburger for Concordia University.

More information on the instructor: https://hybrid.concordia.ca/jbrambur/

Follow @jbramburger7 on Twitter for updates.