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MATH30370

Academic Year 2024/2025

Markov Chains (MATH30370)

Subject:
Mathematics
College:
Science
School:
Mathematics & Statistics
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Professor Neil O'Connell
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

An introductory course on Markov chains

About this Module

Learning Outcomes:

Knowledge and understanding of the subject

Indicative Module Content:

Definition and examples; Markov property; transition probabilities; hitting times; recurrence and transience; harmonic functions and martingales; invariant distributions; reversible Markov chains; convergence to equilibrium.

Student Effort Hours:
Student Effort Type Hours
Lectures

30
Tutorial

6
Autonomous Student Learning

70
Total

106

Approaches to Teaching and Learning:
Lectures, tutorials, homework assignments

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Pre-requisite:
MATH10120 - Linear Algebra Apps to Econ, MATH10130 - Intro to Analysis (E&F), MATH10320 - Mathematical Analysis, MATH10340 - Linear Algebra 1 (MPS), STAT20110 - Introduction to Probability, STAT20110 - Introduction to Probability

Additional Information:
DN200 students: MATH10320, MATH10340 and STAT20110 E&F students: MATH10130, MATH10120 and STAT20110


 

Assessment Strategy  
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered

Not yet recorded.

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Autumn Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

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