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. Thanks for watching! 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.