MATH30370 Markov Chains

Academic Year 2022/2023

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
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 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
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.