A 2.1 Honours degree or equivalent with a substantial mathematics component (at least equivalent to Level-1 courses in mathematics and Level-2 courses in calculus and linear algebra at the University of Glasgow). Previous study of statistics is not required. International students with academic qualifications below those required should contact our partner institution, Glasgow International College, who offer a range of pre-Masters courses. Further information regarding academic entry requirements: email@example.com
Months of entry
This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.
- The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
- Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
- The University of Glasgow’s School of Mathematics and Statistics is ranked 4th in Scotland (Complete University Guide 2015).
- Our Statistics MSc programmes benefit from close links lecturers have with industry, and non-governmental organisations such as NHS and SEPA.
- You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
- You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
- You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
- Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.
- With a 94% overall student satisfaction in the National Student Survey 2014, the School of Mathematics and Statistics combines both teaching excellence and a supportive learning environment.
Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.
Core courses (compulsory)
- Bayesian statistics
- Generalised linear models
- Introduction to R programming
- Probability 1
- Regression models
- Statistical inference 1
- Statistics project and dissertation.
Optional courses (six chosen, but at least one course must be from Group 1)
- Data analysis
- Professional skills.
- Computational inference
- Data management and analytics using SAS
- Design of experiments
- Environmental statistics
- Financial statistics
- Functional data analysis
- Machine learning
- Multivariate methods
- Spatial statistics
- Statistical genetics
- Stochastic processes
- Time series.
1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting courses is subject to approval by the Programme Director.
Summer (May – August)
Statistics project and dissertation (60) - assessed by a dissertation.
- To complete the MSc degree you must undertake a project worth 60 credits. This is a project chosen by you to investigate a challenging statistical problem, where you will investigate the background to the project; identify relevant statistical methodology, formulate and implement an appropriate analysis plan, present your work orally and in a dissertation.
- The project will integrate the subject knowledge and generic skills that you will acquire during your Masters.
- We offer a wide range of projects, and each student is allocated an individual project. We take your preferences into account when we allocate the projects.
- You will also have the opportunity to propose your own project, subject to academic approval.
Please find below some example projects:
- Spectral analysis of Avian EEG
- Investment funds
- Comparing Classification Methods on Near Infrared and Nuclear Magnetic Resonance Spectroscopic Data
Furthermore for students hoping to continue into research, we have five major research groups:
- Biostatistics and Statistical Genetics
- Environmental Statistics
- Computational Statistics and Inference
- Statistical Modelling
- Scholarship of Learning and Teaching in Statistics
Most MSc students choose projects offered by these groups, giving them an opportunity to go on to PhD study.
Information for international students
IELTS: overall score 6.5; no sub-test less than 6.0; ibTOEFL: 92; no sub-test less than 20. CAE: 176 overall; no sub-test less than 169 CPE: 176 overall; no sub-test less than 169. PTE Academic: 60; no sub-test less than 59
Fees and funding
Qualification and course duration
Course contact details
- Postgraduate Admissions Team