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 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.
- Commercially relevant course.
- Course content is aligned with the requirements of the commercial analysis sector.
- Dissertation topics are generated in part by commercial partners.
- Teaching involves widely used commercial software packages (SAS, SPSS).
- The popular open-source tool (R) is also used.
The programme consists of two semesters with taught components which include a mixture of short, intensive 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 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.
The modules in this programme have varying methods of delivery and assessment.
- 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.
- Computing in Statistics: aims to teach computer programming skills, including principles of good programming practice, with an emphasis on statistical computing.
- Introductory Data Analysis: covers essential statistical concepts and analysis methods relevant for commercial analysis.
- 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.
- Software for Data Analysis: covers the practical computing aspects of statistical data analysis focusing on packages most widely used in the commercial sector.
- Statistical Modelling: covers the main aspects of linear models and generalized linear models.
Students choose one optional module, which can be chosen from the School's modules at level 3000 or above.
- Bayesian Inference
- Computing in Mathematics
- Design of Experiments
- Financial Mathematics
- Markov Chains and Processes
- Mathematical Biology 1
- Population Genetics
- Quantitative Risk Management
- Sampling Theory
- Spatial Processes
- Statistical Inference
- Time Series Analysis
- Advanced Combinatorics
- Independent Study Module
- Mathematical Biology 2
- Mathematical Statistics
Computer Science modules
In addition, students may take modules from the School of Computer Science that are consistent with the degree. Representative examples of these modules are:
- Data Intensive Systems
- Database Management Systems
- Information Visualisation and Visual Analytics
Optional modules are subject to change each year, and some may only allow limited numbers of students.
MSc students complete a 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.
The modules listed here are indicative, and there is no guarantee they will run for 2019 entry.
Graduates from this programme typically seek employment as analysts within a company, research body, government, or as statistical consultants.
Recent graduates 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 in building their employability skills.
- 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.
The qualifications listed are indicative of 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.
- two original signed academic references,
- academic transcripts and degree certificates,
- English language requirements certificate,
- letter of intent (optional).
There are many potential scholarships or support schemes available to postgraduates.
Recent Graduate Discount
The University of St Andrews offers a 10% discount in postgraduate tuition fees to students who are eligible to graduate or who have graduated from St Andrews within the last three academic years and are starting a postgraduate programme with the University of St Andrews.
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