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Advanced Statistics

**This programme qualifies for the prestigious Data Lab Masters Scholarships. The award covers full tuition fee costs. For further information please see: Data Lab Masters Scholarships.
www.gla.ac.uk/scholarships/datalabmastersscholarship/**

This Masters in Advanced Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.

**Contact: pgadmissions@glasgow.ac.uk
September start
MRes: 12 months full-time**

**WHY THIS PROGRAMME**

Statistical analysis and data mining is ranked 2nd in the Top 10 Most In-Demand Hard Skills 2018, Linkedin.

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 research groups have strong connections to external organisations such as NHS, SEPA, CEH and others.

Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.

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.

You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.

Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.

This programme qualifies for the prestigious Data Lab Masters Scholarships available for Scottish/EU students.

**PROGRAMME STRUCTURE**

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.

**Courses include (twelve chosen)**
- Advanced Bayesian methods

- Advanced data analysis

- Bayesian statistics

- Biostatistics

- Computational inference

- Data analysis

- Data management and analytics using SAS

- Design of experiments

- Environmental statistics

- Flexible regression

- Financial statistics

- Functional data analysis

- Generalised linear models

- Introduction to R programming

- Linear mixed models

- Machine learning

- Multivariate methods

- Principles of probability and statistics

- Professional skills

- Spatial statistics

- Statistical genetics

- Stochastic processes

- Time series

- Statistics project and dissertation.

**Summer (May - August)**
Statistics project and dissertation (60) - assessed by a dissertation

**Programme alteration or discontinuation**
The University of Glasgow endeavours to run all programmes as advertised. In exceptional circumstances, however, the University may withdraw or alter a programme. For more information, please see: Student contract.
www.gla.ac.uk/myglasgow/senateoffice/studentcontract/

**CAREER PROSPECTS**
Data is becoming an ever increasing part of the modern world, yet the talent to extract information and value from complex data is scarce. There is a massive shortage of data-analytical skills in the workforce. Statistical analysis and data mining is ranked 2nd in the Top 10 Most In-Demand Hard Skills 2018 by LinkedIn. This programme opens up a multitude of career opportunities and/or boosts your career trajectory.
Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.

Entry requirements

Master of Research - MRes: A first degree equivalent to a UK Upper Second Class Honours degree, normally 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).

Graduates who only have A-Level Mathematics (at grade A or better), or equivalent, may also be admitted to the programme. However such candidates are required to work through self-study material provided and attend a pre-sessional course on Elementary Mathematics (to be taught in the two weeks preceding the start of the teaching period of semester 1).

Course modules

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.

Courses include (twelve chosen)

Advanced Bayesian methods
Advanced data analysis
Bayesian statistics
Biostatistics
Computational inference
Data analysis
Data management and analytics using SAS
Design of experiments
Environmental statistics
Flexible regression
Financial statistics
Functional data analysis
Generalised linear models
Introduction to R programming
Linear mixed models
Machine learning
Multivariate methods
Principles of probability and statistics
Professional skills
Spatial statistics
Statistical genetics
Stochastic processes
Time series
Statistics project and dissertation.
Summer (May - August)
Statistics project and dissertation (60) - assessed by a dissertation

Assessment methods

Dissertation.

Qualifications

Qualification Study mode Start month Fee Fee locale Course duration
Master of Research - MRes Full-time September 2019 7,650 (Year 1) England 12 Months
Master of Research - MRes Full-time September 2019 7,650 (Year 1) Wales 12 Months
Master of Research - MRes Full-time September 2019 19,300 (Year 1) International 12 Months
Master of Research - MRes Full-time September 2019 7,650 (Year 1) EU 12 Months
Master of Research - MRes Full-time September 2019 7,650 (Year 1) Northern Ireland 12 Months
Master of Research - MRes Full-time September 2019 7,650 (Year 1) Scotland 12 Months

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