I am learning markov chain/process from the university. My professor is using the book Markov Chains from J.R. Norris. So far i found this book very hard for me to understand the meaning of the theorems (because i am very bad at proofing), anyone has better recommendations on the book (more easy examples to illustrate the properties and theories and how to use the theories to calculate solutions)?
2026-03-28 19:37:57.1774726677
Books for Markov
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A few recommendations, all of which can be obtained for free via the links below:
Random Walks and Electric Networks by Doyle and Snell. Very good book that is accessible at an undergraduate level and explains the intuition behind Markov chains quite well. However, it's the lightest on proofs of all my recommendations.
Markov Chains and Mixing Times by Levin, Peres, and Wilmer. More advanced than the last suggestion, but is accessible, well-written, and proves theorems. (Disclosure: David Levin was my PhD advisor.)
Probability on Trees and Networks by Lyons and Peres -- specifically, chapters 1-3.
Probability: Theory and Examples by Durrett -- specifically, chapter 5. This was the book from which I learned most of my advanced probability theory, and I liked it quite a lot. It may be hard to jump into chapter 5 depending on how much measure-theoretic probability you've seen, though.