MSc in Applied Statistics and Datamining
St Andrews, United Kingdom
MSc
DURATION
1 year
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
07 Aug 2027
EARLIEST START DATE
Sep 2027
TUITION FEES
GBP 25,880 *
STUDY FORMAT
On-Campus
* overseas / home: £11,680
Key Summary
About: The PGDip/MSc in Applied Statistics and Datamining at The University of St Andrews is a taught programme from the School of Mathematics and Statistics for students with a quantitative degree. It teaches statistical data analysis and data‑mining methods aligned with commercial analysis using SAS, SPSS and R. Dissertations are partly set by commercial partners; school hosts research groups and supports progression to PhD study.
Career Outcomes: Career opportunities include analyst, consultant, data‑science roles; recent employers include American Express, Goldman Sachs, PwC and RBS. Graduates work in finance, consulting, biomedical research, clinical trials, pharmaceuticals, conservation and government, and pursue PhDs.
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.
Course details
The PGDip/MSc in Applied Statistics and Datamining is a 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
- 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 modules published below are examples of what has been taught in previous academic years and may be subject to change before you start your program.
Compulsory
- Advanced-Data Analysis: covers modern modeling methods for situations where the data fails to meet the assumptions of common statistical models and simple remedies do not suffice
- Applied Statistical Modelling using GLMs: covers the main aspects of linear models and generalized linear models, including model specification, various options for model selection, model assessment, and tools for diagnosing model faults
- Introductory Data Analysis: covers essential statistical concepts and analysis methods relevant to commercial analysis
- Knowledge Discovery and Datamining: covers many of the methods found under the banner of data mining, building from a theoretical perspective but ultimately teaching practical application
- Multivariate Analysis: introductory and advanced training in the applied analysis of multivariate data
- Software for Data Analysis: covers the practical computing aspects of statistical data analysis focusing on widely used packages, including data-wrangling and visualization.
Optional Undergraduate modules
Students choose one optional module, which can be chosen from the School's modules at level 3000 or above.
Undergraduate-level modules
- Bayesian Inference
- Classical Statistical Inference
- Computational Numerical Analysis
- Computing in Statistics
- Design of Experiments
- Financial Mathematics
- Introduction to Mathematical Computing
- Markov Chains and Processes
- Population Dynamics Models in Mathematical Biology
- Population Genetics
- Quantitative Risk Management
- Sampling Theory
- Spatial Statistics
- Time Series Analysis
Optional Postgraduate modules
Postgraduate-level modules
- Advanced Bayesian Inference
- Advanced Combinatorics
- Estimating Animal Abundance and Biodiversity
- Independent Study Module
- Mathematical Oncology
- Medical Statistics
- Modelling Wildlife Population Dynamics
- Spatial Models and Pattern Formation in Mathematical Biology
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
Optional modules are subject to change each year and require a minimum number of participants to be offered; some may only allow limited numbers of students.
Dissertation
MSc students complete a dissertation during the final three months of the course to be submitted near the end of August. Dissertations are supervised by members of the teaching staff who will advise on the choice of subject and provide guidance throughout the progress of the dissertation. Many topics are in collaboration with companies and other external bodies.
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.
Teaching
Teaching format
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.
Support
The School of Mathematics and Statistics is well equipped with personal computers and laptops, a parallel computer and an on-site library.
The University of St Andrews is committed to attracting the very best students, regardless of financial circumstances.
The University of St Andrews offers postgraduate scholarships and other financial awards. These may be held in addition to external funding or awards from a government body. These may also cover (fully or partially) tuition fees, maintenance (living costs including accommodation), or both.
Scholarships are available based on academic merit and financial need. There are scholarships available for both home and overseas fee status. The scholarship team recommends reading the terms of each award carefully and applying to a range of funding sources.
Postgraduate scholarships
Postgraduate study is an investment in your intellectual development and career potential. The University of St Andrews provides scholarships to help as many students as possible continue in higher education.
Scholarship availability may depend on your area of study or fee status (for example, whether you are a 'Home' or 'Overseas' student).
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:
- American Express
- Aviva
- Capital One
- Goldman Sachs
- Lloyds
- PwC
- RBS
- Scottish and Southern Energy
- Tesco Bank
- TSB
- Vodafone
- Biomedical research, clinical trials and pharmaceuticals
- Wildlife and conservation managers including the Wildlife Conservation Society (WCS).
Further study
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:
- Applied Mathematics (Vortex Dynamics Group, Solar and Magnetospheric Theory Group)
- Pure Mathematics (Analysis Group, Algebra and Combinatorics Group)
- Mathematical Biology (Mathematical Oncology, Cell Migration and Tissue Growth)
- Statistics (Statistical Ecology, Statistical Medicine and Molecular Biology, and Statistical Methodology).