- Module code: ST208
- Module name: Mathematical Methods
- Department: Statistics
- Credit: 12
Module content and teaching
This is a course of techniques which are in everyday use in probability and statistics, and which are essential to a proper understanding of any second or third year course in these subjects. It will provide the mathematical background for optimization, convergence, regression and best approximation and to develop mathematical thinking.
Principal learning outcomes
At the end of the course students will be familiar with and be able to apply the following concepts and techniques:a) multivariate calculus; multiple integration, calculation of volumes, under surfaces; change of variable formule and Fubinis Theorem; partial derivatives, critical points and extrema; constrained optimization; b) eigenvalues/eigenvectors; diagonalisation and Jordan normal form; characteristic polynormals; constant co-efficient differential equations; orthogonal bases and orthonormalisation; generalised Fourier co-efficients; quadratic forms; projections; Spectral Decomposition Theorem; c) metrics; open, closed and compact sets; convergence and continuity in metric spaces.
Timetabled teaching activities
3 hours of lectures per week. 1 tutorial per fortnight starting in week 3.
|Assessment group||Assessment name||Percentage|
|12 CATS (Module code: ST208-12)|
|D (Assessed/examined work)||Assessed Course Work||20%|
|Examination - April||80%|
This module is available on the following courses:
- Undergraduate Mathematics and Statistics (BSc MMathStat) (G1G3) - Year 2
- Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (G300) - Year 2
- Undergraduate Data Science (G302) - Year 2
- Undergraduate Mathematics and Statistics (BSc) (GG14) - Year 2
- Undergraduate Mathematics,Operational Research,Statistics and Economics (Y602) - Year 2
- Undergraduate Discrete Mathematics (G4G1) - Year 2
- Undergraduate Discrete Mathematics (G4G3) - Year 2