An upper second class Honours degree or equivalent with a substantial statistics component (equivalent to a Combined Honours degree in statistics and another subject at the University of Glasgow). Further information regarding academic entry requirements: firstname.lastname@example.org
Months of entry
This Masters in Advanced Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.
· The University of Glasgow’s School of Mathematics and Statistics is ranked 4th in Scotland (Complete University Guide 2015).
· 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.
· 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.
You will choose six courses each semester, depending on your prior knowledge of statistics and subject to the approval of the programme leader.
Courses are chosen from an extensive list, including:
· Advanced Bayesian methods
· Bayesian statistics
· Computational inference
· Data analysis
· Design of statistical investigations
· Environmental statistics
· Functional data analysis
· Generalised linear models
· Introduction to R
· Multivariate methods
· Principles of probability and statistics
· Professional skills
· Sampling and databases
· Spatial statistics
· Statistical data mining
· Statistical genetics
· Stochastic processes
· Time series
· Data-analysis project (leading to 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:
· From DNA sequences to phylogenetic trees to the Bayesian skyline plot
· Bayesian model selection in systems biology
For students hoping to continue into research, we have five major research groups:
Most MSc students choose projects offered by these groups, giving them an opportunity to go on to PhD study.
Information for international students
General English language requirements IELTS 6.5 (with no subtest less than 6) iBT TOEFL 92 (with no less than 21 in Listening & writing, 22 in reading, 23 in speaking)
Fees and funding
Qualification and course duration
Course contact details
- Postgraduate Admissions Team