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MA3211 - Mathematical Modelling and Differential Equations

Credit points: 3
Year: 2023
Student Contribution Band: Band 1
Administered by:

This subject provides students with hands-on mathematical modelling skills for problems that involve dynamical systems. Emphasis will be on mathematical/computer models that will be parameterized with real-world data, such that they can be used to learn about or predict changes over time in the real world. The modelling skills and mathematical techniques learned can be applied to many areas, and we will look at examples from disciplines such as ecology and demography (population growth and decline over time), social sciences (changes among social states), physical models and epidemiology (spread of infectious diseases). You will gain experience in applying mathematical models to real-world problems, by going through the steps of the modelling cycle: from translating a societal or scientific question into a mathematical model to analysing the model and interpreting the results in the context of the original problem. This subject is suitable for students interested in postgraduate industry work or in a research pathway that involves modelling, and for students interested in (applied) mathematics (incl. education, engineering, biology).

Learning Outcomes

  • translate a verbal problem into an algebraic, numerical, visual or conceptual model of a system that can be analysed to understand and predict changes in natural systems over time;
  • construct a mathematical model and employ analytical, graphical, and computational tools, to analyse the behaviour of models under changing conditions, particularly by solving difference and differential equations;
  • parameterize a model with real data, also utilizing tools from statistics/ probability theory and validate models and interpret their outcomes, recognising strengths and limitations.

Subject Assessment

  • Oral > Presentation 1 - (15%) - Individual
  • Weekly Assignments - (25%) - Individual
  • Written > Problem task - (60%) - Individual.
Assumed
Knowledge:
Some computer programming skills (MatLab, R, or any other language) is useful, students lacking this skill are expected to follow a bootcamp at start of subject.
Prerequisites: MA2000 AND (MA2210 OR MA2201)

Availabilities

Townsville, Study Period 1, Internal
Census Date 23-Mar-2023
Coordinator: Dr Martijn van de Pol
Lecturers: Assoc. Professor Roslyn Hickson, Dr Martijn van de Pol.
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 26 hours lectures
  • 39 hours workshops
  • assessment and self-directed study

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.