Course syllabus

Matematisk modellering
Mathematical Modelling

FMAA10, 3 credits, G1 (First Cycle)

Valid for: 2012/13
Decided by: Education Board 1
Date of Decision: 2011-03-23

General Information

Main field: Technology.
Compulsory for: Pi1
Language of instruction: The course will be given in Swedish


The aim of the course is to arouse awareness of the problems of mathematical modelling, i.e., what it means to create quantitative models which can give understanding of phenomena in reality. A further aim is that the student should learn to master some general tools and structures which can be used in modelling, and learn engineering ways of thinking. The course should also provide further acquaintance with Matlab and its use for simulation and computation. Furthermore, the course should develop the student's abilities in oral and written presentation.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

- be able to clearly explain and use the basic concepts of mathematical modelling, in particular be able to explain what a mathematical model is.

- be able to describe and informally explain the process of mathematical modelling, including identification of the problem, formulation, analysis, computation, simulation and feed-back.


Competences and skills
For a passing grade the student must

be able to, independently or in a group, apply the mathematical modelling process on simple and realistic, but vaguely formulated problems, of which some are connected to environmental issues. More specifically, the student should show good ability to:


independently, using appropriate documentation, be able to write Matlab programs to solve mathematical problems within the framework of the course.

in writing as well as orally, with proper terminology, in a well-structured manner and with clear logic be able to explain the solution to a modelling problem.

Judgement and approach
For a passing grade the student must

develop an attitude to the world around us and mathematics, where the use of mathematics in quantitative descriptions of reality seems natural and possible.

be able to tolerate redundance in or missing data, and in such cases to have an engineering attitude in making considerations.


Modelling: The couplings between model and reality. Validation of a model. Some modelling tools. Simple simulations using Matlab.


Examination details

Grading scale: UG
Assessment: Written and oral report of project work, carried out individually and in groups. Compulsory attendance at the project reports.


Required prior knowledge: FMA420/FMA421 Linear algebra. The first part of the course FMAA01/FMAA05.
The number of participants is limited to: No
The course overlaps following course/s: FMA045

Reading list

Contact and other information

Course coordinator: Studierektor Anders Holst,
Course homepage: