Undergraduate - UnitMTH3310 - Applied mathematical modelling

This unit entry is for students who completed this unit in 2014 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

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6 points, SCA Band 2, 0.125 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered, or view unit timetables.

Level	Undergraduate
Faculty	Faculty of Science
Organisational Unit	School of Mathematical Sciences
Offered	Clayton Second semester 2014 (Day)
Coordinator(s)	Professor Kate Smith-Miles

Synopsis

This unit will broaden students' exposure to the toolkit of applied mathematics techniques required to tackle various problems encountered in real-world modelling. Building on the prerequisite knowledge of linear algebra and multivariable calculus, students will learn methods for solving optimization problems, fitting models to data, stochastic modelling, discrete event simulation, and some elementary queueing theory. Application areas include traffic modelling, image processing, inventory management, logistics and other industrial problems that students will have the opportunity to consider. Assessment will include working in teams to solve real-world problems, and presenting the results to the client.

Outcomes

On completion of this unit students will be able to:

Understand specific basic knowledge and display key technical skills in optimisation, model fitting, simulation, and queueing theory, and their applications;
Develop, apply, integrate and generate knowledge through abstraction and by using high-level critical thinking skills to analyse and solve mathematical problems;
Apply knowledge of mathematics and sound mathematical modelling to a range of applications across science, medicine, economics or engineering;
Collect, organise, analyse and interpret quantitative information meaningfully, using mathematical and/or statistical tools as appropriate to the sub-discipline of specialisation;
Demonstrate skills in the written and oral presentation of a mathematical argument that enable mathematical concepts, processes and results to be communicated effectively to diverse audiences;
Work both individually and collectively with staff and colleagues on the synthesis of mathematical knowledge and the application of mathematical skills to problem solving.