MA2MODNU-Mathematical Modelling

Module Provider: Mathematics and Statistics
Number of credits: 10 [5 ECTS credits]
Level:5
Terms in which taught: Spring term module
Pre-requisites: MA0MANU Mathematical Analysis and MA1LANU Linear Algebra and MA1DE1NU Differentiable Equations I
Non-modular pre-requisites: Some basic knowledge for programming with Matlab, R, Excel or similar.
Co-requisites:
Modules excluded:
Current from: 2020/1

Module Convenor: Dr Zuowei Wang

Email: zuowei.wang@reading.ac.uk

Type of module:

Summary module description:

This module will cover topics related to mathematical modelling, e.g. in the areas of science, engineering, and finance.

The Module lead at NUIST is Dr Yan Feng.

Aims:

To develop student’s problem-solving skills by applying mathematical techniques to solve real world problems across a broad range of scientific, engineering and financial topics, such as Newton’s laws of motion, calculations of population growth, loan interest etc.

Assessable learning outcomes:

By the end of this module students are expected to be able to:

• Demonstrate skills to build mathematical models for given practical problems;


• Derive and solve equations implied by appropriate applications using mathematical techniques;


• Dimensional analysis;


• Calculus;


• Ordinary differential equations;


• Linear Algebra.

Additional outcomes:

Examine and visualise the model solutions by using mathematical and statistical programming skills, such as Matlab, Lingo and R.

Outline content:

This module will be delivered in the following steps

1. Model building;


2. Dimensional analysis;


3. Applications of first order ordinary differential equations in topics such as calculations of population growth, loan interest etc.;


4. Applications of systems of ordinary differential equations in topics such as population or predator-prey problems;


5. Applications of second order ordin ary differential equations in topics such as dynamics (Newton’s laws of motion.

Brief description of teaching and learning methods:

Lectures plus tutorials, as well as programming practicals.

Contact hours:

Ìý	Autumn	Spring	Summer
Lectures		52
Tutorials		8
Practicals classes and workshops		8
Guided independent study:	Ìý	Ìý	Ìý
Ìý Ìý Wider reading (independent)		12
Ìý Ìý Wider reading (directed)		8
Ìý Ìý Exam revision/preparation		12
Ìý	Ìý	Ìý	Ìý
Total hours by term	0		0
Ìý	Ìý	Ìý	Ìý
Total hours for module	100

Summative Assessment Methods:

Method	Percentage
Written exam	80
Set exercise	20

Summative assessment- Examinations:

2 hours.

Summative assessment- Coursework and in-class tests:

One examination and a number of assignments.

Formative assessment methods:

Problem sheets.

Penalties for late submission:

The Module Convenor will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day[1] (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at:
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

A mark of 40% overall.

Reassessment arrangements:

One examination paper of 2 hours duration in August/September - the resit module mark will be the higher of the exam mark (100% exam) and the exam mark plus previous coursework marks (80% exam, 20% coursework).

Additional Costs (specified where applicable):

Last updated: 4 April 2020