Program start date | Application deadline |
2025-09-01 | - |
Program Overview
Applied Statistics and Datamining (MSc) 2025 entry
Overview
Develop skills to tackle the critical data analytics challenges facing organisations across all sectors.
Key Details
- Application deadline: Thursday 7 August 2025
- Starts: September 2025
- Duration: One year full time
- School: School of Mathematics and Statistics
Fees
- UK: £12,030
- Rest of the world: £25,900
Why Study This Course?
This course is a rewarding next step for those with a foundation in quantitative elements who wish to gain statistical data analysis skills.
- Gain skills in high demand by the commercial analysis sector
- Work with leading business partners during your studies
- Advance your knowledge of widely used software packages such as Python and R
Teaching
A mix of short, intensive courses and more traditional lectures.
Class Sizes
Typically from 15 to 50 students.
Dissertation
MSc students complete a dissertation project during the final three months, often in collaboration with companies and other external bodies.
Assessment
A mix of continuous assessment and end-of-semester exams.
Modules
The St Andrews degree structure is designed to be flexible. You study compulsory modules delivering core learning together with optional modules you choose from the list available that year.
Compulsory Modules
- 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 Statistical Modelling using GLMs: covers the main aspects of linear models and generalised 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 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.
- 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 visualisation.
Optional UG Modules
Students choose two optional modules, which can be chosen from the School's undergraduate (UG) modules at level 3000 or above.
- Bayesian Inference
- Classical Statistical Inference
- Computational Numerical Analysis
- Computing in Statistics
- Financial Mathematics
- Introduction to Mathematical Computing
- Markov Chains and Processes
- Population Dynamics Models in Mathematical Biology
- Sampling Theory
- Time Series Analysis
Optional PG 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 or assume prior knowledge before taking.
What It Will Lead To
Careers
Graduates typically go on to work as analysts within a company, research body, government, or as statistical consultants.
Elevate Your Career
Recent graduates from the programme have found employment in firms and major financial institutions including:
- AstraZeneca
- DC Thomson
- Lenovo
- Lloyds Bank
Further Your Education
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.
Why St Andrews?
The School of Mathematics and Statistics has active research groups in:
- Applied Mathematics
- Pure Mathematics
- Mathematical Biology
- Statistics
Entry Requirements
- A 2:1 undergraduate Honours degree in a STEM subject or equivalent professional experience. If you studied your first degree outside the UK, see the international entry requirements.
- Demonstrable interest or experience in statistical data analysis in an academic or professional setting.
- English language proficiency. See English language tests and qualifications.
Application Requirements
- A one-page personal statement directly addressing entry requirements, including relevance of previous degree or experience and your interests in statistical analysis
- A CV with a history of your education and employment to date
- Academic transcripts and degree certificates
- Two original signed academic or professional references, ideally one academic reference and a professional reference if experience is to be considered
Scholarships and Funding
We are committed to supporting you through your studies, regardless of your financial circumstances. You may be eligible for scholarships, discounts or other support:
- GREAT Scholarship
- St Andrews Sanctuary Scholarship
- St Leonard's funding opportunities
- Graduate discount (15% off tuition fees)
Mathematics and Statistics scholarships
Accreditation
Graduates of the MSc programme can apply to the Royal Statistical Society for the professional status of Graduate Statistician (GradStat) without the need for further examination.
University of St. Andrews
Overview:
The University of St. Andrews is Scotland's first university, established in 1413. It is renowned for its academic excellence, particularly in postgraduate studies, and consistently ranks among the top universities in the UK.
Services Offered:
The university provides a comprehensive range of services for students, including:
MySaint:
A student portal for accessing various resources and information.Moodle:
An online learning platform for course materials and communication.Library:
A well-equipped library with extensive resources and study spaces.MMS:
A student support system for managing academic and personal matters.Accommodation:
On-campus housing options for students.Fees and Funding:
Information on tuition fees and financial aid opportunities.Scholarships:
Various scholarships available for eligible students.Student Life and Campus Experience:
The university offers a vibrant and diverse campus experience, characterized by:
Close-knit community:
A strong sense of belonging fostered by the small town setting.Academically stimulating environment:
Opportunities for intellectual growth and engagement.Active research:
Involvement in cutting-edge research projects.International community:
A diverse student body from around the world.Numerous extracurricular activities:
Opportunities for social interaction and personal development.Key Reasons to Study There:
Top-ranked university:
Consistently ranked among the best in the UK.World-leading research:
Access to cutting-edge research facilities and resources.Excellent postgraduate programs:
A wide range of taught Masters degrees and online courses.Strong academic reputation:
A prestigious institution with a long history of academic excellence.Supportive and welcoming community:
A close-knit environment that fosters a sense of belonging.Academic Programs:
The university offers a wide range of academic programs across various disciplines, including: