University of St Andrews

University of St Andrews

Applied Statistics and Data Mining

The PGDip/MSc in Applied Statistics and Datamining is a commercially relevant programme of study providing students with the statistical data analysis skills needed for business, commerce and other applications. The programme is aimed at individuals with a good degree containing quantitative elements, who wish to gain statistical data analysis skills relevant to business, commerce and other applications. The programme offers preparation for commercial data analysis, a commercially relevant course of study that has content aligned with the requirements of partners in the commercial analysis sector and strongly applied bias, with an emphasis on application in the commercial sector. Dissertation topics are generated in part by our commercial partners. Teaching is usually within widespread commercial, rather than research, software packages for example SAS and SPSS. Teaching consists of a mixture of short, intense courses with a large proportion of continuous assessment and more traditional lecture courses with end of semester exams.

Entry requirements

Undergraduate degree, 2.1 or equivalent, with some mathematical or statistical content. All applicants whose 1st language is not English should be fluent in written and oral English. Preferred credentials are IELTS 7; TOEFL: paper-based 600; computer-based 250; internet-based 100.

Course modules

The modules in this programme have varying methods of delivery and assessment. For more details of each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue which is for the 2016-2017 academic year; some elements may be subject to change for 2017 entry.

Compulsory modules:
Statistical Modelling: covers the main aspects of linear models (LMs) and generalized linear models (GLMs).
Data Analysis: covers essential statistical concepts, data manipulation and analysis methods, and software skills in commercial analysis packages.
Advanced Data Analysis: covers modern modelling methods for situations where the data fails to meet the assumptions of common statistical models and simple remedies do not suffice.
Applied Multivariate Analysis: introductory and advanced training in the applied analysis of multivariate data.
Knowledge Discovery and Datamining: covers many of the methods found under the banner of "datamining", building from a theoretical perspective but ultimately teaching practical application.
Optional modules: Students choose two optional modules, which can be chosen from across the School's undergraduate and postgraduate-level modules.
Computing in Statistics is strongly recommended unless you have extensive experience.

Undergraduate-level modules:

Computing in Statistics,
Computing in Mathematics,
Time Series Analysis,
Markov Chains and Processes,
Population Genetics,
Bayesian Inference,
Spatial Processes,
Financial Mathematics,
Mathematical Biology 1,
Project in Mathematics / Statistics,
Statistical Inference,
Sampling Theory,
Design of Experiments.
Postgraduate-level modules:

Advanced Statistical Inference,
Estimating Animal Abundance,
Advanced Bayesian Inference,
Mathematical Biology 2,
Independent Study Module,
Professional Skills for Mathematical Scientists,
Advanced Project in Mathamatics / Statistics.
In addition, students may take modules from the School of Computer Science that are consistent with the degree. Representative examples of these modules are:
Database Management Systems,
Information Visualisation and Visual Analytics.
Dissertation:MSc students complete a 15,000-word dissertation during the final three months of the course to be submitted by the end of August. Dissertations are supervised by members of teaching staff who will advise on the choice of subject and provide guidance throughout the progress of the dissertation.

Assessment methods

Continuous assessment, end of semester exams, and dissertation/project of up to 15,000 words.

Sponsorship information

Carnegie-Cameron bursaries; entrant accommodation bursary; Formula Santander postgraduate scholarship; recent graduate discount; Thomas and Margaret Roddan Trust bursary; SAAS postgraduate funding.


Qualification Study mode Start month Fee Course duration
MSc Full-time September 2017 GBP 6,800 per Year 1 (EU) 1 years
MSc Full-time September 2017 GBP 6,800 per Year 1 (England) 1 years
MSc Full-time September 2017 GBP 16,250 per Year 1 (International) 1 years
MSc Full-time September 2017 GBP 6,800 per Year 1 (Northern Ireland) 1 years
MSc Full-time September 2017 GBP 6,800 per Year 1 (Scotland) 1 years
MSc Full-time September 2017 GBP 6,800 per Year 1 (Wales) 1 years

Campus details

Campus name Town Postcode Region Main campus Campus Partner
University of St Andrews St Andrews KY16 9AX Scotland

Key information

Postgraduate Admissions Officer
Telephone number: 
01334 462156