MTH3310 - Applied mathematical modelling - 2018

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 reducing real world problems into mathematical ones. The students will then learn a broad range of analytical techniques focused on some commonly encountered systems in modelling. Some of these topics include solving optimization problems, fitting models to data, analysing dynamical systems and partial differential equation models. Application areas include traffic modelling, image processing, inventory management, logistics and other scientific and industrial problems. Students will have the opportunity to consider a specific real world problem using their own mathematical modelling approach alongside a client/supervisor. Assessment will include working in teams to solve real-world problems, and presenting the results to the client.

On completion of this unit students will be able to:

1. Understand specific basic knowledge and display key technical skills in optimisation, model fitting, dynamical systems, and partial differential equations, and their applications;
2. Develop, apply, integrate and generate knowledge through abstraction and by using high-level critical thinking skills to analyse and solve mathematical problems;
3. Apply knowledge of mathematics and sound mathematical modelling to a range of applications across science, medicine, economics or engineering;
4. Collect, organise, analyse and interpret quantitative information meaningfully, using mathematical and/or statistical tools as appropriate to the sub-discipline of specialisation;
5. 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;
6. Work both individually and collectively with staff and colleagues on the synthesis of mathematical knowledge and the application of mathematical skills to problem solving.

Examination (3 hours): 60% (Hurdle)

Continuous assessment: 40%

Hurdle requirement: To pass this unit a student must achieve at least 50% overall and at least 40% for the end-of-semester exam.

One 1-hour lecture, one 2-hour lecture and one 2-hour support class per week

See also Unit timetable information

Applied mathematics

Mathematical statistics

Mathematics