Advanced Stochastic Modelling

For honours courses please contact the School Office.

Description

This course is part of the course offerings at Honours (Level IV) within Applied Mathematics. Stochastic modelling plays an integral role in the analysis of many real-world systems. For example, in designing a telecommunications network it is important to be able to calculate performance measures such as mean utilisation of a resource, probability of packet loss, or expected time until a bu?er becomes empty. All of these are stochastic quantities that have to be derived via models that include randomness in their formulation. Similar examples can be given from most areas of science. Assumed knowledge: Basic Probability (as obtained through, for example Mathematics for Information Technology I or Introduction to Mathematical Statistics II) Markov chains (as obtained through, for example, Applied Probability III).

Objective

At the end of this subject, students will be equipped with all the tools necessary to develop and analyse stochastic models that arise in a broad range of physically motivated problems.

Content

Nigel Bean Lecturer for this course

Delivery

2 one-hour lectures per week plus tutorials as required.

Assessment

Three hour examination (85%) and three written assignments (15%).

Graduate attributes

• Applying mathematical knowledge (1)
• Interpreting data and drawing conclusions (2)
• Formulating mathematical problems (3)
• Problem solving skills (4)
• Flexibility in working environment (5)
• Team participation and leadership (7)
• Self-directed study (8)
• Career development (9)

Linkage past

APP MTH 2008, Operations Research II, APP MTH 3001 Applied Probability III and APP MTH 3016 Telecommunication Systems Modelling III are all very useful background

Linkage present

No present linkages have been noted.

Linkage future

This course is not recorded as prequisite for other courses.

Restrictions

None.

Recommended text

None.