Originally I planned to spend 2 weeks talking about Markov chains with the goal of learning about Markov Chain Monte Carlo (MCMC) methods used in Bayesian statistics. Unfortunately, we lost one week due to coronavirus, and I think most of you would rather have some time to catch up on old homework. So all of this week's material is optional. If you are interested in spending this week learning a little about Markov Chains, keep reading!

Both our current textbook Probability and Statistics - The Science of Uncertainty, 2nd edition, by Evans and Rosenthal and last semester's textbook Introduction to Probability, 8th edition, by Grinstead & Snell have chapters about Markov chains. Of the two, I think that Grinstead & Snell's chapter is a little easier to read and has better exercises.


Monday, April 20

Optional. If you want to learn about Markov chains, then

On Wednesday and Friday, I'll suggest additional exercises from Sections 11.2 and 11.3 in Grinstead & Snell.


Wednesday, April 23

Optional Topic: Absorbing Markov chains.


Friday, April 25

Optional Topic: Irreducible (aka Ergodic) Markov chains.