# MATH30370 Markov Chains

An introductory course on Markov chains

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Curricular information is subject to change

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
Autonomous Student Learning

70

Lectures

30

Tutorial

6

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

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

Assessment Strategy
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Class Test: In-class test(s) Throughout the Trimester n/a Standard conversion grade scale 40% No

20

Examination: Written exam 2 hour End of Trimester Exam No Standard conversion grade scale 40% No

80

Carry forward of passed components
Yes

Resit In Terminal Exam
Autumn Yes - 2 Hour
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.

Spring

Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 09:00 - 10:50
Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 10:00 - 10:50
Spring