Linear Algebra 2.5 Markov Chains

In this video, we explore the concept of Markov chains. We use a probability transition matrix that represents the probability of a member of the population moving from one “state” to another “state” to determine the population distribution after n iterations.

Video Chapters:
0:00 Introduction
0:07 A Sample Problem
1:27 Stochastic matrices
4:46 Which Matrices are Stochastic?
6:44 nth State Matrix of a Markov Chain
9:15 Practice Finding the nth State of a Markov Chain
12:22 Back to the Satellite TV Example (Leading up to Steady State)
14:43 Regular Stochastic Matrix
16:32 Finding a Steady State Matrix
22:32 Practice Finding a Steady State Matrix
26:14 Absorbing State
29:13 Absorbing Markov Chains
31:50 Finding a Steady State Matrix For Absorbing Markov Chains
36:17 Practice Finding a Steady State Matrix For Absorbing Markov Chains
43:24 Up Next

Textbook: Elementary Linear Algebra 8e, Ron Larson

Slide Decks: https://bellevueuniversity-my.sharepoint.com/:f:/g/personal/kbrehm_bellevue_edu/IgDVnTt2BohsRLsMfseN5FijAXYDd49YlIkHeq5cfmCxG2g?e=ZwTt3c

Playlist: https://youtube.com/playlist?list=PLl-gb0E4MII1RjTV2GegmXFTJwTrek8OI&si=g3Xc3yHB5GkmxMF4