Markov Chains
Presenter(s)
Jordyn Hurley
Files
Description
Markov Chains model stochastic processes and are used to predict random events and their outcomes. In Markov Chains, I explored the different techniques found to demonstrate practical uses within real world scenarios. A good reminder for Markov Chains is in each event, the probability depends on the state of the previous event that occurred. Markov Chains can be applied to different theories to help analyze complex ideas. The theories include:- Transition matrices- Multi-step transition probabilities and distribution vectors- Regular Markov Chains- Absorbing Markov Chains
Publication Date
4-23-2025
Project Designation
Capstone Project
Primary Advisor
Rebecca J. Krakowski
Primary Advisor's Department
Mathematics
Keywords
Stander Symposium, College of Arts and Sciences
Institutional Learning Goals
Vocation; Scholarship
Recommended Citation
"Markov Chains" (2025). Stander Symposium Projects. 4053.
https://ecommons.udayton.edu/stander_posters/4053
Comments
1:15-2:30, Kennedy Union Ballroom