Skip to content

Breadcrumbs navigation

Statistics

Understanding patterns and structure, and developing the tools with which to analyse them, is the primary focus of all mathematics. Whether the patterns relate to physical or biological phenomena or to the structure of mathematics itself, the primary aim is to describe, categorise, and understand the processes involved.

A student of Statistics will be concerned with developing the analytic techniques and skills necessary to explore some of these fascinating areas of research.

Courses

Undergraduate

Statistics BSc (Hons)
Statistics MA (Hons)
Statistics MMath (Hons)

Joint degree options 

The Statistics BSc (Hons) and the Statistics MA (Hons) programmes can be taken with another subject as part of a joint degree.

Postgraduate

Taught

Statistics MSc
Applied Statistics and Datamining MSc
Data-Intensive Analysis MSc
Mathematics MSc

 

PhDs

Please contact a supervisor in your research area to inquire about PhD opportunities.

Visit St Andrews

If you are interested in studying at St Andrews, join us at an open day to explore the town, find out about our courses and meet current students.

 Undergraduates

Booking for the spring visiting days is now open. To book onto a visiting day, please select your preferred choice of date and complete the booking form.

Postgraduates

  • Wednesday 8 March 2017
  • November 2017 - date to be confirmed.

Booking for the spring visiting days is now open.

Sign up

Statistics research areas

The School of Mathematics and Statistics promotes a friendly research atmosphere with cross-flow of ideas while providing the depth and breadth necessary to pursue major scientific programmes at an international level. There are strong links between different research groups within the School as well as interdisciplinary links with theoretical computer science, biology, astronomy and geoscience.

Research in Statistics is divided into two major areas:

Statistical inference

The Statistical Inference Research Group conducts research on method development for spatial point process modelling, Bayesian statistics, inferential methods for mark-recapture and plant-capture studies, and the development of empirical smoothing techniques.

Research staff:

  • Professor Rosemary Bailey: statistical design of experiments including block designs, randomization and multi-tiered experiments.
  • Professor David Borchers: statistical methods for estimating wildlife population parameters, including abundance, distribution and trends from survey data.
  • Dr Janine Illian: spatial statistics, spatial point processes and spatio-temporal models.
  • Dr Monique MacKenzie: development of methods that permit the identification of spatially explicit change, and methods which adequately capture nonlinearities on a variety of spatial scales, while accounting for the temporal elements of the data.
  • Dr Michail Papathomas: Bayesian inference; bioinformatics; statistical genetics.
  • Dr Len Thomas: use of computer intensive methods to fit and compare stochastic models of wildlife population dynamics; development of methods and software for estimating the size, density and distribution of wild animal and plant populations.

Statistical ecology

The Statistical Ecology Research Group focuses on research into biodiversity, capture-recapture studies, distance sampling, quantifying the environmental impact of underwater sound, movement modelling, bioacoustic data analysis, and spatially adaptive smoothing methods.

Research staff:

  • Professor David Borchers: statistical methods for estimating wildlife population parameters, including abundance, distribution and trends from survey data.
  • Professor Stephen Buckland: statistical ecology, especially modelling population dynamics, wildlife resource management, wildlife population assessment, distance sampling and biodiversity monitoring.
  • Dr Carl Donovan: quantifying the environmental impact of underwater sound; simulation-based impact assessment for complex scenarios based on underwater sound-based disturbance.
  • Dr Monique MacKenzie: development of methods that permit the identification of spatially explicit change, and methods which adequately capture nonlinearities on a variety of spatial scales, while accounting for the temporal elements of the data.
  • Dr Len Thomas: use of computer intensive methods to fit and compare stochastic models of wildlife population dynamics; development of methods and software for estimating the size, density and distribution of wild animal and plant populations.

Statistics research centres and institutes

Centre for Interdisciplinary Research in Computational Algebra (CIRCA)
CIRCA undertakes mathematical research with computer assistance, develops new techniques for computation in abstract algebra, and develops and distributes software implementing these techniques.

Centre for Research into Ecological and Environmental Modelling (CREEM)
CREEM develops and applies advanced mathematical and statistical methods to practical problems in biology, ecology and geography.

Statistics research portal

 

Careers for graduates in Statistics

Statistics postgraduates hold positions at leading universities or companies in areas as diverse as business administration, financial markets, biomedical research, fisheries laboratories, wildlife conservation and many more.

Those who study a degree in Statistics gain skills in clear logical thinking, deductive reasoning, data handling and IT skills; therefore, graduates in Statistics are in high demand and have a wide selection of opportunities, including:

  • research
  • teaching
  • merchant banking
  • insurance
  • computer consulting
  • civil service
  • finance.

See recent graduate employment case studies.

Work experience

Work experience is invaluable when it comes to securing graduate-level employment. There are a number of Mathematics-specific opportunities for students to gain work experience:

  • Gain work experience overseas by applying for a placement through IAESTE (the International Association for the Exchange of Students for Technical Experience). 
  • Become a committee member of SUMS, a student-run mathematics society. 
  • Apply for summer research scholarships: Carnegie Trust or Nuffield Foundation.

Funding opportunities

There is a range of funding opportunities available to prospective undergraduates, postgraduates and PhD students.

Undergraduate

Various scholarships are available to prospective undergraduate students.

Undergraduate scholarships

Postgraduate students

The University of St Andrews offers various postgraduate funding opportunities.

Postgraduate taught scholarships

PhD students

Find out more about funding at PhD level.

Funding for PhD students

Awards

REF 2014

The School of Mathematics and Statistics was ranked second in Scotland for the quality of research, with 91% of its research activity rated world-leading or internationally excellent in the Research Excellence Framework 2014.

Athena SWAN Bronze Award

The School of Mathematics and Statistics was awarded an Athena SWAN Bronze Award in 2014 for recognising and encouraging practices that reduce inequalities in the work place.

Contact

School of Mathematics and Statistics
University of St Andrews
Mathematical Institute
North Haugh
St Andrews
KY16 9SS

Phone: +44 (0)1334 46 2344
Email: maths@st-andrews.ac.uk

Mathematics and Statistics website

Mathematics and Statistics research portal