ADVANCED STATISTICS MSC

ADVANCED STATISTICS MSC

Next Date: September

Why choose this program ?

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

Why this programme

- 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.
- The Masters in Advanced Statistics is accredited by the Royal Statistical Society.
- 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.

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. 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. Recent graduates have been employed by Lloyds Banking Group, Equifax, Kohler, Moodys and Globality.

Modality

£

Price Remarks

Open registration Limited spots

2.1 Hons (or non-UK equivalent) in A degree with substantial Mathematics and Statistics components with at least 20 credit bearing modules in Statistics and University Level Mathematics at an average grade of pass.

- A substantial Mathematics component is required which is at least equivalent to Level-1 courses in Mathematics and Level-2 courses in Calculus and Linear Algebra at the University of Glasgow.

- A substantial component of Statistics methodology is required, including at least Honours-level courses in probability theory, likelihood-based inference and the theory of linear models.

Apply for partial scholarships


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. 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. Recent graduates have been employed by Lloyds Banking Group, Equifax, Kohler, Moodys and Globality.

SYLLABUS

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.

Students are required to take 1 compulsary taught course and select 11 courses from the optional courses in semesters 1 and 2. We recommend you take 6 courses per semester.

Note: course choice is subject to timetabling constraints and should be discussed with your advisor of studies.

Semester 1

Optional courses

- Advanced Bayesian Methods (Level M)
- Biostatistics (Level M)
- Flexible Regression (Level M)
- Linear Mixed Models (Level M)
- Multivariate Methods (Level M)
- Principles of Probability and Statistics (Level M)
- Stochastic Processes (Level M)
- Introduction to statistical programming in R and Python

Semester 2

Core course

- Data Analysis Skills (Level M)

Optional courses

- Bayesian Statistics (Level M)
- Design of Experiments (Level M)
- Environmental and Ecological Statistics (Level M)
- Functional Data Analysis (Level M)
- Spatial Statistics (Level M)
- Statistical Genetics (Level M)
- Advanced Predictive Models

Project (summer)

- Advanced Statistics Project and 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.

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