Applied Statistics and Datamining (PGDip/MSc) 2017 entry
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.
Application deadline
Course type
Postgraduate; leading to a Postgraduate Diploma (PGDip) or Master of Science (MSc)
Course duration
Nine months full time (PGDip) or one year full time (MSc)
Entry requirements
A good 2.1 undergraduate Honours degree in Mathematics, Statistics or in an area with substantive mathematical or statistical content. If you studied your first degree outside the UK, see the international entry requirements.
English language proficiency. See English language tests and qualifications.
The qualifications listed are indicative minimum requirements for entry. Some academic Schools will ask applicants to achieve significantly higher marks than the minimum. Obtaining the listed entry requirements will not guarantee you a place, as the University considers all aspects of every application including, where applicable, the writing sample, personal statement, and supporting documents.
Tuition fees
UK and EU: £7,500
Overseas: £17,090
Application deadline
Application requirements
- CV
- two original signed academic references
- academic transcripts and degree certificates
- English language requirements certificate
- letter of intent (optional).
If you started this programme in 2016, you can find information about 2016 entry on the 2016 Applied Statistics and Datamining page. Information about all programmes from previous years of entry can be found in our archive.
For more guidance, see supporting documents and references for postgraduate taught programmes.
Watch current students and staff discuss the teaching facilities, research opportunities and student life at Scotland's first university.
Course information
The PGDip/MSc in Applied Statistics and Datamining is a one-year taught programme run by the School of Mathematics and Statistics. The course is aimed at those with a good degree containing quantitative elements who wish to gain statistical data analysis skills.
Highlights
- The course is commercially relevant and has content aligned with the requirements of partners in the commercial analysis sector. Dissertation topics are generated in part by our commercial partners.
- Teaching includes widespread commercial software packages (SAS, SPSS) along with popular open-source tools (R).
Teaching format
The programme consists of two semesters with taught components which include a mixture of short, intense courses with a large proportion of continuous assessment and more traditional lecture courses with end of semester exams.
For those on the MSc, the taught component will be followed by a 15,000-word dissertation project taking place during the last three months of the course.
The School of Mathematics and Statistics is well equipped with personal computers and laptops, a parallel computer and an on-site library.
Further particulars regarding curriculum development.
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 level 3000-or-above modules.
Computing in Statistics is strongly recommended unless you have extensive R 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 Mathematics / 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
The modules listed ran in the academic year 2016–2017 and are indicative of this course. There is no guarantee that these modules will run for 2017 entry. Take a look at the most up-to-date modules in the module catalogue.
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.
If students choose not to complete the dissertation requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma. By choosing an exit award, you will finish your degree at the end of the second semester of study and receive a PGDip instead of an MSc.
Conferences and events
There are a number of different seminars held each week in the School of Mathematics and Statistics. These include:
Pure Mathematics
Pure Mathematics Colloquia
Algebra and Combinatorial Seminars
Analysis Group Seminars
Applied Mathematics
Applied Mathematics Seminars
Solar and Magnetospheric Theory Group Seminars
Vortex Dynamics Group Seminars
Statistics
Statistics Seminars
CREEM and NCSE Seminars
Funding
There are many potential scholarships or support schemes available to postgraduates.
Recent Graduate Discount
The University of St Andrews offers a 10% reduction in tuition fees for students who have graduated during the last three years and are now starting a postgraduate programme.
Thomas and Margaret Roddan Trust (Postgraduate)
Competitive awards ranging from £500 to £3,000 are usually available for postgraduates undertaking either taught or research courses in Scotland.
After the MSc
Research degrees
The MSc in Applied Statistics and Datamining prepares students for further postgraduate studies in statistical data research, and many graduates of the programme continue their education by enrolling in PhD programmes at St Andrews or elsewhere.
The School of Mathematics and Statistics has active research groups in:
- Pure Mathematics (Analysis Group, Algebra and Combinatorics Group)
- Applied Mathematics (Vortex Dynamics Group, Solar and Magnetospheric Theory Group, Mathematical Biology Group)
- Statistics (Statistical Ecology Group, Statistical Inference Group).
Careers
Graduates from this programme typically seek employment as analysts within a company, research body, government, or as statistical consultants.
Our recent graduates at Masters level have found employment in:
- large consulting firms and major financial institutions including Scottish and Southern Energy, RBS, Aviva, Lloyds, TSB, PwC, Capital One, Vodafone, American Express, Goldman Sachs, Tesco Bank and many others.
- biomedical research, clinical trials and pharmaceuticals.
- wildlife and conservation managers including the Wildlife Conservation Society (WCS).
The Careers Centre offers one-to-one advice to all students on a taught postgraduate course and offers a programme of events to assist students to build their employability skills.
Contact
School of Mathematics and Statistics
Mathematical Institute
North Haugh
St Andrews
Fife KY16 9AL
Scotland
Phone: +44 (0)1334 46 2344
Email: maths-pgstats@st-andrews.ac.uk
Admission to the University of St Andrews is governed by our Admissions policy.
Curriculum development
As a research intensive institution, the University ensures that its teaching references the research interests of its staff, which may change from time to time. As a result, programmes are regularly reviewed with the aim of enhancing students' learning experience. Our approach to course revision is described online. (PDF, 72 KB).
Tuition fees
The University will clarify compulsory fees and charges it requires any student to pay at the time of offer. The offer will also clarify conditions for any variation of fees. The University’s approach to fee setting is described online. (PDF, 84 KB).
St Andrews has two postgraduate prospectuses - one for taught courses and one for research programmes. Both prospectuses are available for you to view and download.