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4000-level modules

MT4003 Groups
MT4004 Real Analysis
MT4005 Linear and Nonlinear Waves

MT4111 Symbolic Computation
MT4112 Computing in Mathematics
MT4113 Computing in Statistics

MT4501 Topics in the History of Mathematics

MT4507 Classical Mechanics
MT4508 Dynamical Systems
MT4509 Fluid Dynamics
MT4510 Solar Theory
MT4511 Asymptotic Methods

MT4513 Fractal Geometry
MT4514 Graph Theory
MT4515 Functional Analysis
MT4516 Finite Mathematics
MT4519 Number Theory
MT4526 Topology

MT4527 Time Series Analysis
MT4528 Markov Chains and Processes
MT4530 Population Genetics
MT4531 Bayesian inference
MT4537 Spatial Processes

MT4539 Quantitative Risk Management

MT4551 Financial Mathematics
MT4552 Mathematical Biology 1
MT4553 Theory of Electric and Magnetic Fields

MT4599 Project in Mathematics/Statistics (final year of BSc/MA degree only)

MT4606 Statistical inference
MT4607 Generalized Linear Models and Data Analysis
MT4608 Sampling Theory
MT4609 Multivariate Analysis
MT4614  Design of Experiments
MT4794 Joint Dissertation (30cr)

MT4796 Joint Project (30cr)


MT4003  Groups

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 9.00 am Mon (even weeks), Tue and Thu
Description

This module introduces students to group theory, which is one of the central fields of the 20th century mathematics. The main theme of the module is classifying groups with various additional properties, and the development of tools necessary in this classification. In particular, the students will meet the standard algebraic notions, such as substructures, homomorphisms, quotients and products, and also various concepts peculiar to groups, such as normality, conjugation and Sylow theory. The importance of groups in mathematics, arising from the fact that groups may be used to describe symmetries of any mathematical object, will be emphasised throughout the module.

Prerequisites MT3600 or (MT2002 and MT3501) or MT2505
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10), 1 tutorial and 1 examples class (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Dr M R Quick
Lecturer Dr M R Quick

Syllabus

  • Groups: definitions, examples;
  • Subgroups, generating sets, cosets, Lagrange's Theorem;
  • Normal subgroups, quotient groups, homomorphisms, kernels and images, the Isomorphism Theorems, the Correspondence Theorem;
  • Direct products, the Classification of Finite Simple Groups;
  • Simplicity of the alternating groups An for n ≥ 5;
  • The centre, conjugation, commutators, centralizers, normalizers;
  • Sylow's Theorem;
  • Classification of groups of small order.

Assumed knowledge

  • It will be assumed that students are familiar with calculating with permutations (as presented in MT2002, MT2505 or MT1003).
  • It will be assumed that students have met the definition of a group and some of the basic ideas, though these will be reviewed briefly at the beginning of the course.

Reading list

  • R.B.J.T. Allenby, Rings, Fields and Groups: An Introduction to Abstract Algebra, Butterworth-Heinemann, 1991: Chapters 5 and 6.
  • W. Ledermann, Introduction to Group Theory, Oliver and Boyd.
  • John S. Rose, A Course on Group Theory, Dover 1994: up to Chapter 6.
  • T.S. Blyth & E.F. Robertson, Algebra Through Practice: A Collection of Problems in Algebra with Solutions, Book 5: Groups, CUP, 1995.
  • Thomas W. Hungerford, Algebra, Holt, Rinehart and Winston, 1974: Chapters 1 and 2.
  • I.N. Herstein, Topics in Algebra, Second Edition, Wiley, 1975: Chapter 2.
  • Derek J.S. Robinson, A Course in the Theory of Groups, Second Edition, Springer, 1996: some parts of the early chapters.
  • Joseph J. Rotman, An Introduction to the Theory of Groups, Fourth Edition, Springer, 1995: some parts of the early chapters.


MT4004  Real and Abstract Analysis

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 11.00 am Mon (even weeks), Tue and Thu
Description

This module continues the development of real analysis that was begun in MT2502 and continued through MT3502. Topics covered will include limits and continuity in metric spaces, differentiation in higher dimensions and the theoretical underpinning of Fourier series. This module will present some of the highlights of the study of analysis, such as Baire's Category Theorem, the Contraction Mapping Theorem, the Weierstrass Approximation Theorem, and the Inverse Function Theorem.

Prerequisites MT3502
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10), 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Prof L Olsen
Lecturer Prof L Olsen

Syllabus

  • Metric spaces, continuity and completeness: Recall the basic definitions of metric spaces and continuity; complete metric spaces; examples.
  • Applications of complete metric spaces: (1) Contraction Mapping Theorem; examples including, for example, solutions to integral equations.  (2) Baire’s Category Theorem; examples including, for example, (i) Existence of continuous and nowhere differentiable functions; (ii) The rationals is not a Gδ set.  (3) Weierstrass approximation Theorem
  • Continuity in metric spaces: (1) Functions of bounded variation; (2) Absolutely continuous functions.
  • Differentiation in higher dimensions: (1) Definition of differentiation in higher dimensions and examples; (2) The Mean Value Theorem in Rn
  • Applications of differentiation in higher dimensions: (1) Inverse Function Theorem; (2) The Implicit Function Theorem; (3) Sard’s Theorem.
  • Differentiation in one dimension: Lebesgue’s theorem on differentiability almost everywhere
  • Fourier Series: Definitions; summability and pointwise convergence of Fourier series and uniform convergence of Fourier series.

Reading list

  • S Krantz & H Parks, Geometric Integration Theory, Birkhauser, 2008.
  • W Rudin, Principles of Mathematical Analysis, Third Edition, McGraw-­‐‑Hill, 1976.
  • M Spivak, Calculus on Manifolds, 1968.
  • K Stromberg, An Introduction to Classical Real Analysis, Wadsworth & Brooks, 1982.


MT4005  Linear and Nonlinear Waves

Credits 15.0
Semester 1
Academic year 2017/8
Timetable 11.00 am Mon (even weeks), Tue and Thu
Description

This module gives an introduction to wave motion and its importance in many areas of applied mathematics. It begins with a discussion of the linear approximation for small amplitude waves and discusses properties of these such as dispersion relations, phase and group velocities, dissipation and dispersion. Some nonlinear effects such as wave steepening are then treated and an introduction given to some of the equations, for example Burger's and Korteweg de Vries, which are used to model nonlinear wave propagation.

Prerequisites (MT2003 or MT2506 or PH3081) and (MT3503 or MT3504)
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Dr A N Wright
Lecturer Dr A N Wright


MT4111  Symbolic Computation

Credits 15.0
Semester 2
Academic year 2018/9
Timetable 9.00 am Mon (odd weeks), Wed and Fri
Description

This module aims to enable students to use a computer as a tool in their other modules and to turn naturally to a computer when solving mathematical problems. The module aims to illustrate the following points: computation allows one to conduct mathematical experiments; computation allows one to collect data about a problem being studied. This is similar to the way other scientists work. It is easier to try several different approaches to a problem and see which works. The computer is not intelligent; intelligence comes from the user. The user thinks, the user interprets, the computer calculates.

Prerequisites Any of MT3501 - MT3506
Antirequisites MT5611
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 practical session (weeks 2 - 11)
Assessment 2-hour Written Examination = 70%, Coursework = 30%
Module coordinator TBC
Lecturer TBC

MT4111 runs in alternate years.


MT4112  Computing in Mathematics

Credits 15.0
Semester 1
Academic year 2017/8
Timetable 9.00 am Mon (even weeks), Tue and Thu
Description

This module is intended to introduce students to FORTRAN and the writing of computer codes to implement mathematical algorithms. The module includes a basic introduction to FORTRAN, and the implementation of mathematical algorithms in a well-documented FORTRAN program. Students are required to complete a project in addition to sitting the examination.

Prerequisites either pre- or co-requisites MT3501, MT3503 or MT3504
Antirequisites MT5612, Honours or Joint Honours Programme in Computer Science.
Lectures and tutorials 2.5 lectures (weeks 1 - 10).
Assessment 2-hour Written Examination = 70%, Coursework: Project = 30%
Module coordinator Prof D H Mackay
Lecturer Prof D H Mackay, Dr T Elsden

MT4112 runs in alternate years.


MT4113  Computing in Statistics

Credits 15.0
Semester 1
Academic year 2017/8
Timetable 12.00 noon Mon (odd weeks) and Wed, 12.00 noon – 2.00 pm Fri
Description

The aim of this module is to teach computer programming skills, including principles of good programming practice, with an emphasis on statistical computing. Practical work focusses on the widely-used statistical language and environment R. Practical skills are developed through a series of computing exercises that include (1) modular programming; (2) manipulating data; (3) simulating data with specific statistical properties, (4) investigating behaviour of statistical procedures under failure of statistical assumptions.

Prerequisites pre- or co-requisite MT2508 or MT2004
Antirequisites MT3607
Lectures and tutorials 1.5-hour lectures (x 10 weeks), 2-hour practical classes (x 10 weeks)
Assessment 2-hour Written Examination = 40%, Coursework = 60%
Module coordinator Dr L J Thomas
Lecturer Dr L J Thomas, Dr E Rexstad

Syllabus

  • Computer arithmetic; algorithms; introduction to R.
  • Control structures.
  • Modular programming; programming practice; code testing.
  • Computer intensive statistics: bootstrapping; randomisation tests.
  • Optimisation.
  • Reproducible analysis.


MT4501  Topics in the History of Mathematics

Credits 15.0
Semester 1
Academic year 2017/8
Timetable 12.00 noon Mon (odd weeks), Wed and Fri
Description

The aim of this module is to give students an insight into the historical development of mathematics. Topics to be covered may include some of: the development of algebra, the origins of the calculus, the history of logarithms, the work of some individual mathematicians.

Prerequisites either pre- or co-requisites: Any of MT3501 - MT3508 or MT3606
Antirequisites MT5613
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment Written Examination = 50% (2 x 1-hour class tests), Coursework: Project = 50%
Module coordinator Dr I J Falconer
Lecturer Dr I J Falconer, Dr C P Bleak, Prof M A J Chaplain

MT4501 runs in alternate years.


MT4507  Classical Mechanics

Credits 15.0
Semester 2
Academic year 2018/9
Timetable 10.00 am Mon (even weeks), Tue and Thu
Description

The object of this module is to introduce students to some of the ideas and mathematical techniques used in understanding the behaviour of dynamical systems that obey Newton's Laws. These notions are arguably the foundations of physics and applied mathematics. The module will include: Newton's laws of motion; conservative forces; central forces; non-inertial/accelerating frames of reference; dynamics of a system of particles; mechanics of a rigid body; Euler's equations; Lagrange's equations; Hamilton's equations.

Prerequisites (MT2003 or MT2503 or PH3081) and MT3504
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator TBC
Lecturer TBC

MT4507 runs in alternate years.


MT4508  Dynamical Systems

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 10.00 am Mon (even weeks), Tue and Thu
Description

This module aims to introduce students to the basic ideas of the modern theory of dynamical systems and to the concepts of chaos and strange attractors. The module will include: period doubling; intermittency and chaos; geometrical approach to differential equations; homoclinic and heteroclinic orbits; Poincaré sections; the Smale horseshoe mapping; centre manifold theory.

Prerequisites MT3504
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Dr V Archontis
Lecturer Dr V Archontis

MT4508 runs in alternate years.


MT4509  Fluid Dynamics

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 11.00 am Mon (even weeks), Tue and Thu
Description

This module provides an introduction to the theory of incompressible fluid dynamics, which describes the motion of liquids and gases at speeds small compared to the sound speed. Special attention is paid to a precise foundation of the various conservation laws that govern fluid dynamics, as this provides a convenient framework in which to study specific examples as well as extensions of the basic theory.

Prerequisites (MT2506 and MT3504) or MT3601
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment Written Examination = 100% (2-hour final exam = 90%, class test = 10%)
Module coordinator Dr M Carr
Lecturer Dr M Carr


MT4510  Solar Theory

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 11.00 am Mon (odd weeks), Wed and Fri
Description

The object of this module is to describe the basic dynamic processes at work in the Sun, a subject which is being enlivened by dramatic new results from space missions.

Prerequisites (MT2506 and MT3504) or MT3601
Antirequisites MT4504, MT5804
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Prof I De Moortel
Lecturer Prof I De Moortel


MT4511  Asymptotic Methods

Credits 15.0
Semester 1
Academic year 2018/9
Timetable 9.00 am Mon (even weeks), Tue and Thu
Description

This module is designed to introduce students to asymptotic methods used in the construction of analytical approximations to integrals and solutions of differential equations.

Prerequisites MT3504
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator TBC
Lecturer TBC

MT4511 runs in alternate years.

Syllabus

  • Introduction to ideas of expansion using a small parameter, review of basic expansions, definition of order symbols;
  • Expansions of integrals, Watson's lemma, the Laplace method and method of stationary phase;
  • Asymptotic methods for differential equations, multiple scales;
  • Matched asymptotic expansions;
  • The WKB method.

Assumed knowledge

  • A basic understanding of limits and convergence.
  • A good knowledge of basic expansions is essential - for example Taylor series, Binomial series.
  • Students must also be able to solve simple o.d.e.s and be able to do basic integration.

Reading list

  • Perturbation Methods - E.J. Hinch
  • Asymptotic Analysis - J.D. Murray
  • Pertubation Methods for Engineers and Scientists - C.M. Bender & S.A. Orszag
  • Perturbation Methods for Engineers and Scientists - A.W. Bush
  • Pertubation Methods - A.H. Nayfeh


MT4513  Fractal Geometry

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 12.00 noon Mon (even weeks), Tue and Thu
Description

The aim of this module is to introduce the mathematics used to describe and analyse fractals and to show how the theory may be applied to examples drawn from across mathematics and science. The module discusses the philosophy and scope of fractal geometry; and may include topics such as dimension, representation of fractals by iterated function systems, fractals in other areas of mathematics such as dynamical systems and number theory, Julia sets and the Mandelbrot set.

Prerequisites (MT2503 or MT2001) and any one of MT3501 - MT3504
Antirequisites MT5813
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Prof K J Falconer
Lecturer Prof K J Falconer

MT4513 runs in alternate years.

The module will introduce the mathematics used to describe and analyse fractals, and to show how the theory may be applied to examples drawn from across mathematics and science. The approach will have a geometric emphasis and the treatment will precise though not over-formal.

Syllabus

  • The philosophy and scope of fractal geometry.
  • The concept of dimension.
  • Box-counting and Hausdorff dimensions, their properties and calculation in simple cases.
  • Representation of fractals by iterated function schemes, relation to dimensions and applications
  • Fractals in dynamical systems, number theory, and other areas of mathematics.
  • Iteration of complex functions, Julia sets and the Mandelbrot set.

Reading list

Books providing an overview of fractal geometry:

  • Fractals - A Very Short Introduction, Kenneth Falconer (Oxford U.P., 2013)
  • Introducing Fractals - A Graphic Guide, N. Lesmoir-Gordon, W. Rood & R. Edny (Icon Books, 2009)
  • The Fractal Geometry of Nature, Benoit Mandelbrot (W.H. Freeman, 1982)

Books at the level of the course

  • Fractal Geometry: Mathematical Foundations and Applications, Kenneth Falconer (John Wiley, 3rd Ed, 2014)    
  • Chaos and Fractals, H.-O. Peitgen, H. Jurgens & D. Saupe (Springer-Verlag, 1992)
  • Fractals Everywhere, Michael Barnsley (Academic Press, 2nd Ed, 1993)
  • Measure, Topology and Fractal Geometry, G.A. Edgar (Springer-Verlag, 1990)


MT4514  Graph Theory

Credits 15.0
Semester 1
Academic year 2018/9
Timetable 10.00 am Mon (even weeks), Tue and Thu
Description

The aim of this module is to introduce students to the study of graph theory as a tool for representing connections between data. Topics to be covered may include: basic theory and applications, Eulerian graphs, Hamiltonian graphs, planar graphs, spanning trees and applications, networks, matching problems.

Prerequisites MT1003 or MT2504 or MT2005
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator TBC
Lecturer TBC

MT4514 runs in alternate years.

Syllabus

  • graphs: definition of simple, directed, labelled, and weighted graphs
  • subgraphs, graph homomorphisms, graph homeomorphisms
  • complete graphs, bipartite graphs, trees
  • shortest paths
  • Eulerian cycles, Hamiltonian cycles, planarity, colourability
  • spanning trees
  • Hall's marriage theorem
  • NP complete problems

Assumed knowledge

  • It will be assumed that students are familiar with abstract definitions of mathematical objects and basic formal proofs.


MT4515  Functional Analysis

Credits 15.0
Semester 2
Academic year 2018/9
Timetable 12.00 noon Mon (even weeks), Tue and Thu
Description

This object of this module is to familiarise students with the basic notions of functional analysis, that is analysis on normed spaces and Hilbert space. The module will cover normed spaces, convergence and completeness, operators, Hilbert spaces and may include topics such as spectral theory and the Hahn-Banach theorem.

Prerequisites MT2002 or (MT2501 and MT2502)
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator TBC
Lecturer TBC

MT4515 runs in alternate years.

Syllabus

  • Normed spaces and examples.
  • Bounded linear operators on norm spaces.
  • The operator norm.
  • Completeness.
  • The contraction mapping theorem.
  • Finite dimensional spaces.
  • Spaces of continuous functions.
  • Banach spaces.
  • Inner product spaces and Hilbert spaces.
  • The spectrum of a bounded linear operator.
  • Compact operators.
  • The spectral theorem for compact self-adjoint operators.

Reading list

  • Rynne, B.P. & Youngson, M.A., Linear Functional Analysis, Springer, 2nd Ed 2007.
  • Young, N., An Introduction to Hilbert Space, Cambridge University Press, 1988.
  • Griffel, D.H., Applied Functional Analysis, Dover, 2nd Ed 2002.
  • Bollobas, B, Linear Analysis: An Introductory Course, Cambridge University Press, 2nd Ed 1999.


MT4516  Finite Mathematics

Credits 15.0
Semester 1
Academic year 2017/8
Timetable 10.00 am Mon (even weeks), Tue and Thu
Description

The aim of this module is to introduce students to some topics in the mathematics of combinatorial structures. This theory has wide applications, both in classical mathematics and in theoretical computer science. Topics to be covered may include: coding theory, finite geometries, Latin squares, designs.

Prerequisites MT2504 or MT2505 or MT2002 or MT2005
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Dr C M Roney-Dougal
Lecturer Dr C M Roney-Dougal

MT4516 runs in alternate years.


MT4519  Number Theory

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 10.00 am Mon (even weeks), Tue and Thu
Description

The aim of this module is to introduce students to some important topics in number theory. Topics to be covered may include: prime numbers, cryptography, continued fractions, Pell's equation, the Gaussian integers and writing numbers as sums of squares.

Prerequisites (MT2505 or MT2002) and one of MT3501 - MT3505
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator TBC
Lecturer TBC

MT4519 runs in alternate years.


MT4526  Topology

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 10.00 am Mon (odd weeks), Wed and Fri
Description

This module introduces the ideas of metric and topological spaces. A metric space is simply a set together with a 'distance' between any two points. This idea is pervasive in mathematics: from situations such as the usual distance in n-dimensional space, to the Hamming distance between words in an error-correcting code and the distance between functions approximating a given function. Metric spaces can be thought of as particular instances of topological spaces, where the fundamental concept is that of points being 'close' to each other rather than the precise distance between points. Topological spaces are a powerful generalisation of metric spaces, and have had a profound influence in the development of mathematics. Many examples of metric spaces and topological spaces will be introduced and fundamental ideas within topology will be discussed, including separation axioms, compactness and connectedness.

Prerequisites MT2002 or MT2502 or MT3600 or MT4004
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Dr L S Theran
Lecturer Dr L S Theran

MT4526 runs in alternate years.

Syllabus

  1. Metric spaces, convergence and continuity in metric spaces, complete metric spaces;
  2. Topological spaces, continuity in topological spaces, separation axioms;
  3. Subspaces, product spaces and quotient spaces;
  4. Compactness, the Heine-Borel Theorem, and Tychonoff's Theorem;
  5. Connectedness.

Additional topics may also be covered, for instance, the Contraction Mapping Theorem, and Baire's Category Theorem.

Reading list

  • Sutherland, Introduction to Metric and Topological Spaces
  • Munkres, Topology: a first course
  • Willard, General Topology


MT4527  Time Series Analysis

Credits 15.0
Semester 2
Academic year 2018/9
Timetable 10.00 am Mon (even weeks), Tue and Thu
Description

This module provides an introduction to univariate linear times series models (ARIMA processes) and univariate non-linear times-series models (ARCH and GARCH). The syllabus includes: forecasting methods for constant mean and trend models, the ARIMA class of models (including seasonal ARIMA models), fitting and forecasting ARIMA models, ARCH and GARCH processes.

Prerequisites MT2004 or MT2508
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 0.5 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator TBC
Lecturer TBC

MT4527 runs in alternate years.

Syllabus

  1. Introduction
  2. Basic time series models
  3. Models with trend and seasonality
  4. ARMA models
  5. ARIMA models
  6. ARCH and GARCH models

Reading list

  • P. Brockwell & P. Davis: Introduction to Time Series and Forecasting, Springer Texts in Statistics, 2002
  • R. Tsay: Analysis of Financial Time Series, 3rd ed., Wiley, 2010
  • D.C. Montgomery,  , C.L. Jennings & Kulahci, M.: Introduction to Time Series Analysis and Forecasting, Wiley-Interscience, 2008
  • Box, G.E.P., Jenkins, G.M. & Reinsel, G.: Time Series Analysis - Forecasting and Control, 4th ed., Wiley Series in Probability and Statistics, 2008


MT4528  Markov Chains and Processes

Credits 15.0
Semester 1
Academic year 2017/8
Timetable 11.00 noon Mon (even weeks), Tue and Thu
Description

This module provides an introduction to the theory of stochastic processes and to their use as models, including applications to population processes and queues. The syllabus includes the Markov property, Chapman-Kolmogorov equations, classification of states of Markov chains, decomposition of chains, stationary distributions, random walks, branching processes, the Poisson process, birth-and-death processes and their transient behaviour, embedded chains, Markovian queues and hidden Markov models.

Prerequisites MT2504 or MT2004
Antirequisites MT3706
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 8 tutorials over the semester.
Assessment 2-hour Written Examination = 100%
Module coordinator Prof D L Borchers
Lecturer Prof D L Borchers, Dr V M Popov

MT4528 runs in alternate years.

Syllabus

  • Preliminaries: Introduction to the ideas of stochastic processes and models (including index sets and state space); brief review of probability theory; probability generating functions.
  • Markov chains: Definition; directed graphs; transition probability matrices; Chapman-Kolmogorov equations; classification of states; decomposition of states; periodicity; limiting distributions; stationary distributions.
  • Random walks: gambler's ruin; probability of ruin; absorption probabilities.
  • Branching processes: Galton-Watson process; extinction probabilities; criticality theorem.
  • Markov processes: continuous-time Markov chains; Poisson process; birth/death process; Kolmogorov forward equation.
  • Queueing systems: Kendall notation; special queues.
  • Hidden Markov models: model formulation; basic properties; applications.

Reading list

  • Jones, P. W. and Smith, P. Stochastic processes : an introduction, Arnold/OUP.
  • Stirzaker, D. R. Stochastic processes and models, OUP.
  • Ross, S. M. Introduction to probability models, 9th ed., Academic Press.
  • Norris, J.R. Markov chains, CUP.
  • Grimmett, G. R. and Stirzaker, D. R. Probability and random processes, 3rd ed., OUP.
  • Taylor, H. M. and Karlin, S. An introduction to stochastic modeling, 3rd ed., Academic Press.
  • Zucchini, W. and MacDonald, I. L. Hidden Markov models for time series: an introduction using R. Chapman & Hall.


MT4530  Population Genetics

Credits 15.0
Semester 1
Academic year 2017/8
Timetable 9.00 am Mon (even weeks), Tue and Thu
Description

This module aims to show how the frequencies of characteristics in large natural populations can be explained using mathematical models and how statistical techniques may be used to investigate model validity. The syllabus includes: Mendel's First and Second Laws, random mating and random union of gametes, Hardy-Weinberg equilibrium, linkage, inbreeding, assortative mating, X-linked loci, selection and mutation.

Prerequisites MT2004 or MT2508
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 0.5 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Dr I B J Goudie
Lecturer Dr I B J Goudie

MT4530 runs in alternate years.


MT4531  Bayesian Inference

Credits 15.0
Semester 1
Academic year 2017/8
Timetable 10.00 am Mon (even weeks), Tue and Thu
Description

This module is intended to offer a re-examination of standard statistical problems from a Bayesian viewpoint and an introduction to recently developed computational Bayes methods. The syllabus includes Bayes' theorem, inference for Normal samples; univariate Normal linear regression; principles of Bayesian computational, Markov chain Monte Carlo - theory and applications.

Prerequisites MT3507 or MT3606
Antirequisites MT5831
Lectures and tutorials 24 lectures and 7 practical classes over the semester.
Assessment 2-hour Written Examination = 80%, Coursework = 20%
Module coordinator Dr M Papathomas
Lecturer Dr M Papathomas


MT4537  Spatial Processes

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 10.00 am Mon (even weeks), Tue and Thu
Description

This module will study probabilistic and inferential problems for spatial processes. It commences with a discussion on different types of spatial data. In the context of spatial point processes functional and non-functional summary characteristics for point patterns are considered. Spatial point process models, including homogeneous and inhomogeneous Poisson processes as well as Gibbs processes and Cox processes along with the approaches to parameter estimation and model evaluation, are introduced. Models in geostatistics based on empirical variograms and kirging approaches and spatial models for lattice data (CAR model, Gauss Markov random fields) are also discussed.

Prerequisites MT3507 or MT3606
Antirequisites MT4536
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 4 tutorials over the semester.
Assessment 2-hour Written Examination = 100%
Module coordinator Dr J B Illian
Lecturer Dr J B Illian

MT4537 runs in alternate years.

Syllabus

  1. Types of spatial data
  2. Spatial point processes, exploratory analysis (intensity estimation, indices as summary characteristics, K-function, pair correlation function)
  3. Spatial point processes, modelling (homogeneous and inhomogeneous Poisson process, cluster models, Gibbs processes, Cox processes)
  4. Geostatistics (semivarigrams, exponential, Gaussian, power model, anisotropy)
  5. Spatial models for lattice data (CAR model, Gauss Markov random fields)


MT4539  Quantitative Risk Management

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 12.00 noon Wed, Fri and odd Mon, and 2.00 pm Fri
Description

The module introduces the concept of financial risk and discusses the importance of its regulation. The emphasis is laid on the popular risk measure Value at Risk (VaR). After a brief discussion on asset returns, various modelling techniques - ranging from the simple Historical Simulation to the more advanced ARMA and GARCH models - are presented and applied for the calculation of VaR using real financial data. The aim of this module is to provide a solid basis in risk management for those students considering a career in finance.

Prerequisites MT2504, MT2508
Antirequisites
Lectures and tutorials 2.5 lectures (x 10 weeks), 5 tutorials and 5 practical sessions.
Assessment 2-hour Written Examination = 80%, Coursework = 20%
Module coordinator Dr V Popov
Lecturer Dr V Popov


MT4551  Financial Mathematics

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 10.00 am Mon (odd weeks), Wed and Fri
Description

Students are introduced to the application of mathematical models to financial instruments. The course will include an overview of financial markets and the terminology in common usage but the emphasis will be on the mathematical description of risk and return as a means of pricing contracts and options.

Prerequisites (MT2001 or MT2503) and (MT1007 or MT2004 or MT2504 or EC2003) and MT3504
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Prof D H Mackay
Lecturer Prof D H Mackay

MT4551 runs in alternate years.


MT4552  Mathematical Biology 1

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 9.00 am Mon (even weeks), Tue and Thu
Description

This module will explore real world applications of mathematics to biological problems e.g. harvesting of fish stocks, host-parasitoid systems, predator-prey dynamics, molecular interactions. The mathematical techniques used in the modelling will be nonlinear difference equations and ordinary differential equations. The module will be useful to students who wish to specialise in Applied Mathematics in their degree programme.

Prerequisites MT3504
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 1 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 90%, Coursework (Class Test) = 10%
Module coordinator Dr C Venkataraman
Lecturer Dr C Venkataraman

Continuous assessment

50-minute class test: 10% of final mark

Syllabus

  • Difference equation models of single species (e.g. insect populations; difference equation difference equation models of interacting species models (e.g. host-parasitoid systems, plant-herbivore systems); delay-difference equation models.
  • Differential equation models of single species (including harvesting); differential equation models of interacting species (e.g. Lotka-Volterra system; predator-prey systems); Limit cycles and the Hopf bifurcation theorem.
  • Introductory Systems Biology - intracellular signalling modelling and biochemical reactions; Law of Mass Action; Michaelis-Menten kinetics; Quasi-Steady State Assumption; Matched asymptotics; Metabolic pathways; Autocatalysis and activator-inhibitor systems.

Reading list

  • N.F. Britton, Essential Mathematical Biology, (Springer 2003).
  • J.D. Murray, Mathematical Biology I: An Introduction, (Springer, 3rd ed. 2003).
  • J.D. Murray, Mathematical Biology II: Spatial Models and Biomedical Applications, (Springer, 3rd ed. 2003).
  • L. Edelstein-Keshet, Mathematical Models in Biology, (SIAM Classics in Applied Mathematics, SIAM Publishing 2005).


MT4553  Theory of Electric and Magnetic Fields

Credits 15.0
Semester 2
Academic year 2018/9
Timetable 10.00 am Mon (odd weeks), Wed, Fri
Description

The module will consider the mathematical and physical principles that describe the theory of electric and magnetic fields. It will first describe the basic principles of electrostatics and magneto-statics and following this electrodynamics. Next Maxwell's equations are described along with the properties of electro-magnetic waves in a variety of media. Finally an application to the area of plasma physics is carried out through considering the orbits of charged particles in a variety of spatially and time varying magnetic fields.

Prerequisites MT2503, MT2506 and MT3504
Antirequisites PH3007
Lectures and tutorials 2.5 hours of lectures (x 10 weeks), 1-hour tutorial (x 10 weeks)
Assessment 2-hour Written Examination = 90%, Coursework (class test) = 10%
Module coordinator TBC
Lecturer TBC

MT4553 runs in alternate years.


MT4599  Project in Mathematics / Statistics

Credits 15.0
Semester Whole Year
Academic year 2017/8
Timetable none
Description

The student will choose a project from a list published annually although a topic outwith the list may be approved. Students will be required to report regularly to their supervisor and a report of no more than 5,000 words must be submitted by the end of the April.

Prerequisites
Antirequisites
Lectures and tutorials Typically and on average, 20 mins of project supervisions per week over whole year.
Assessment Coursework = 100%: Project = 80%, Presentation = 20%
Module coordinator Prof C E Parnell
Lecturer

Booklet for MT4599 BSc/MA Honours projects 2017-2018 (PDF, 478 KB)

and the Project allocation form 2017-2018 (PDF, 70 KB)


MT4606  Statistical Inference

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 10.00 am Mon (odd weeks), Wed and Fri
Description

This module aims to show how the methods of estimation and hypothesis testing met in 2000- and 3000-level Statistics modules can be justified and derived; to extend those methods to a wider variety of situations. The syllabus includes: comparison of point estimators; the Rao-Blackwell Theorem; distribution theory; Fisher information and the Cramer-Rao lower bound; maximum likelihood estimation; hypothesis-testing; confidence sets.

Prerequisites MT3507 or MT3606
Antirequisites MT5701
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 0.5 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator Prof A G Lynch
Lecturer Prof A G Lynch

MT4606 runs in alternate years.


MT4607  Generalised Linear Models and Data Analysis

Credits 15.0
Semester 1
Academic year 2018/9
Timetable 9.00 am Mon (even weeks), Tue and Thu
Description

This module aims to demonstrate the power and elegance of unifying a large number of simple statistical models within the general framework of the generalised linear model. It will train students in the interpretation, analysis and reporting of data, when a single response measurement is interpreted in terms of one or a number of other variables.

Prerequisites (MT2001 or MT2503), (MT2004 or MT2508) and either pre- or co-requisite MT3501
Antirequisites MT5753
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 8 tutorials over the semester
Assessment 2-hour Written Examination = 80%, Coursework: Project = 20%
Module coordinator TBC
Lecturer TBC

MT4607 runs in alternate years.

Syllabus

  • Revision of ordinary linear models
  • Exponential family of distributions
  • Formulation of generalized linear models
  • Concept of link function
  • Iterated weighted least squares algorithm
  • Inference
  • Model selection
  • Diagnostics

Reading list

  • Dobson, A. (2008). An Introduction to Generalized Linear Models, Third Edition. Chapman & Hall/CRC
  • McCullagh, P., Nelder, J. (1989). Generalized Linear Models, Second Edition. Chapman and Hall/CRC


MT4608  Sampling Theory

Credits 15.0
Semester 1
Academic year 2018/9
Timetable 10.00 am Mon (odd weeks), Wed and Fri
Description

The aims of this module are to introduce students to and interest them in the principles and methods of design-based inference, to convince them of the relevance and utility of the methods in a wide variety of real-world problems, and to give them experience in applying the principles and methods themselves. By the end of the module students should be able to recognise good and poor survey design and analysis, to decide upon and implement the main types of survey design in relatively straightforward settings, and analyse the resulting survey data appropriately. The syllabus includes fundamentals of design based vs model-based inference, simple random sampling, sampling with replacement, ratio and regression estimators, stratified sampling, cluster sampling and unequal probability sampling.

Prerequisites MT2004 or MT2508
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 8 tutorials over the semester.
Assessment 2-hour Written Examination = 85%, Coursework: Project = 15%
Module coordinator TBC
Lecturer TBC

MT4608 runs in alternate years.


MT4609  Multivariate Analysis

Credits 15.0
Semester 2
Academic year 2018/9
Timetable 10.00 am Mon (odd weeks), Wed and Fri
Description

This module aims to introduce students to the ideas and techniques of multivariate statistical analysis. The syllabus includes mean vectors, covariance matrices, correlation matrices; basic properties of multivariate normal distributions; checking multivariate normality; the likelihood ratio and union-intersection principles for constructing multivariate tests; the one-sample and two-sample Hotelling's T-squared tests; tests on covariance matrices, tests of independence; linear discriminant analysis; principal components analysis; canonical correlation.

Prerequisites MT3507 or MT3606
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and 0.5 tutorial (weeks 2 - 11).
Assessment 2-hour Written Examination = 100%
Module coordinator TBC
Lecturer TBC

MT4609 runs in alternate years.


MT4614  Design of Experiments

Credits 15.0
Semester 2
Academic year 2017/8
Timetable 9.00 am Mon (odd weeks), Wed and Fri
Description

This module introduces a wide range of features that occur in real comparative experiments, such as choice of blocks and replication as well as type of design. It includes enough about the analysis of data from experiments to show what has to be considered at the design stage. It includes consultation with the scientist and interpretation of the results.

Prerequisites (MT2004 or MT2508) and MT3501
Antirequisites
Lectures and tutorials 2.5 lectures (weeks 1 - 10) and either tutorial or practical (weeks 2 - 11).
Assessment 2-hour Written Examination = 80%, Presentation = 10%, Coursework = 10%
Module coordinator Prof R A Bailey
Lecturer Prof R A Bailey

Syllabus

  1. Introduction to concepts in the design of real comparative experiments.
  2. Randomization, replication, power.
  3. Simple linear model, orthogonal subspaces, analysis of variance.
  4. Blocking. Fixed effects or random effects. Orthogonal designs.
  5. Factorial designs. Main effects and interactions. Control treatments.
  6. Row-column designs. Latin squares.
  7. Observational units smaller than experimental units. False replication.
  8. Split-plot designs. Treatment effects in different strata.
  9. Structures defined by families of orthogonal factors. Eigenspaces of highly structured variance-covariance matrices.
  10. Showing factors on a Hasse diagram.  Using the Hasse diagram to calculate degrees of freedom and allocate treatment effects to strata. Skeleton analysis of variance.

Reading list

  • R. A. Bailey, Design of Comparative Experiments, CUP, 2008.
  • D. R. Cox, Planning of Experiments, Wiley 1992.
  • G. W. Cobb, Introduction to Design and Analysis of Experiments, Springer, 1998. 


MT4794  Joint Dissertation (30cr)

Credits 30.0
Semester Whole Year
Academic year 2017/8
Timetable To be arranged.
Description

The dissertation must consist of approximately 6,000 words of English prose on a topic agreed between the student and two appropriate members of staff (who act as supervisors). The topic does not have to relate to work covered in previous Honours modules, though it may be helpful to the student if it builds on previous work. The topic and range of sources should be chosen in consultation with the supervisors in order to determine that the student has access to sources as well as a clear plan of preparation. (Guidelines for printing and binding dissertations can be found at: http://www.st-andrews.ac.uk/printanddesign/dissertation/)

Prerequisites A Letter of Agreement.
Antirequisites More than 30 credits in other dissertation / project modules
Lectures and tutorials As per Letter of Agreement.
Assessment As per Letter of Agreement.
Module coordinator As per Letter of Agreement.
Lecturer


MT4796  Joint Project (30cr)

Credits 30.0
Semester Whole Year
Academic year 2017/8
Timetable To be arranged.
Description

The aim of the project is to develop and foster the skills of experimental design, appropriate research management and analysis. The topic and area of research should be chosen in consultation with the supervisors in order to determine that the student has access to sources as well as a clear plan of preparation.

Prerequisites A Letter of Agreement.
Antirequisites More than 30 credits in other dissertation / project modules
Lectures and tutorials As per Letter of Agreement.
Assessment As per Letter of Agreement.
Module coordinator As per Letter of Agreement.
Lecturer