SCQF Level: 10
Course Prerequisite: MAT9K4
Credit Value: 20 (1 module)
This module will be motivated by real-life examples from Biology and Medicine. In part A the concepts underlying the design of experiments and their analysis will be explored. In particular, multivariate methods for describing and analysing many dimensional data will be presented and applied. In part B different mathematical modelling techniques will be studied and applied.
Students should be able to:
A1. Introduction and Sampling Techniques
A2. Linear Models and Analysis of Variance
A3. Crossed & Nested Designs
A4. Multivariate Data
A5. Multivariate Normal Distribution
A6. Principal Components Analysis
A7. Discriminant Analysis
B1. Mathematical modelling: introduction
B2. Discrete time models; equilibria, time delays
B3. Matrices in modelling; Leslie matrix
B4. Continuous time models; equilibria
B5. Multi-species models; symbiotics, predator-prey, SIR model
The ability to formulate problems in statistical terms, to design and then to present, analyse and interpret data. Problem solving; information retrieval; computing; analytical skills; group working; presentational skills; report writing.
There will be three 1-hour lectures and one 1 hour practical per week.
1/3 coursework (2 practical projects) and 2/3 examination.