Program Overview

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MSc Applied Statistics

The MSc Applied Statistics is a conversion course, offering the opportunity to develop skills in statistics and data analysis even if you have never studied statistics before. You'll be supported by members of staff who work directly with industry to develop skills which are relevant to current areas of research including population health and medicine, animal and plant health, finance and business.

Programme Overview

• The programme is designed to provide students with a comprehensive understanding of statistical methods and their applications in various fields.
• Students will gain skills in problem-solving, analysis and manipulation of complex data, and the use of statistical software packages for data analysis and reporting.
• The programme is accredited by the Royal Statistical Society, and MSc graduates may qualify for GradStat status.

Key Facts

• Start date: September
• Accreditation: Royal Statistical Society: MSc graduates may qualify for GradStat status
• Study mode and duration: MSc: 12 months full-time

Why this Course?

Our MSc in Applied Statistics is a conversion course, offering the opportunity to develop skills in statistics and data analysis even if you have never studied statistics before. You'll be supported by members of staff who work directly with industry to develop skills which are relevant to current areas of research including population health and medicine, animal and plant health, finance and business.

Programme Skillset

On the MSc Applied Statistics programme you'll have the opportunity to acquire:

• an in-depth knowledge of modern statistical methods used to analyse and visualise real-life data sets, and the experience of how to apply these methods in a professional setting
• skills in using statistical software packages used in government, industry and commerce
• the ability to interpret the output from statistical tests and data analyses, and communicate your findings to a variety of audiences including health professionals, scientists, government officials, managers and stakeholders who may have an interest in the problem
• problem solving and high numeracy skills widely sought after in the commercial sector
• practical experience of statistical consultancy and how to interact with professionals who require statistical analyses of their data

What you’ll Study

In addition to compulsory modules, there are a range of elective modules, meaning you can tailor the course in line with your career interests.

Semester 1

In semester 1, modules focus on the foundations of statistics. You’ll learn about probability, and basic statistical analysis, as well as developing skills in programming in the statistical programming language R.

Semester 2

In semester 2, modules will build on concepts from year 1. These will focus on methods of analysis that can be applied to specific areas, such as medical trials, risk analysis, and finance.

Semester 3

In semester 3, you'll undertake a research project in which you'll work on a real-life data set, putting the theoretical skills you have learned into practice.

Learning & Teaching

Classes are delivered by a number of teaching methods:

• lectures (using a variety of media including electronic presentations and computer demonstrations)
• tutorials
• computer laboratories
• coursework
• projects

Teaching is student-focused, with students encouraged to take responsibility for their own learning and development. Classes are supported by web-based materials.

Assessment

The form of assessment varies from class to class. For most classes the assessment involves both coursework and examinations.

• The assessment will ask you to demonstrate your statistical knowledge and skills to analyse real world data and interpret the results in the context of the research question
• Projects will involve writing code, interpreting statistical outputs, and producing a report, or presentation outlining the findings from your analysis
• Group work may be undertaken in some classes

Facilities

The Department of Mathematics & Statistics has teaching rooms which provide you with access to modern teaching equipment and University computing laboratories, with all necessary software available.

You'll also have access to a common room facility which gives you a modern and flexible area for individual and group study work and is also a relaxing social space.

The Department of Mathematics & Statistics

At the heart of the Department of Mathematics & Statistics is the University’s aim of developing useful learning. We're an applied department with many links to industry and government. Most of the academic staff teaching on this course hold joint-appointments with, or are funded by, other organisations, including APHA, Public Health and Intelligence (Health Protection Scotland), NHS Greater Glasgow and Clyde and the Marine Alliance for Science and Technology Scotland (MASTS). We bridge the gap between academia and real-life. Our research has societal impact.

Course Content

Throughout your studies, you will take 60 credits of compulsory taught classes, 60 credits of elective taught classes, and in the third (summer) term you'll also undertake your MSc Project (60 credits)

Compulsory Classes

• Foundations of Probability & Statistics (20 credits)
• Data Analytics in R (20 credits)
• Experimental Design (10 credits)
• Multivariate Analysis (10 credits)

Elective Classes

Students are required to take at least 10 credits from List A and the remaining 50 credits can be from List A and/or List B modules.

List A

• Quantitative Risk Analysis (10 credits)
• Bayesian Spatial Statistics (10 credits)

List B

• Survey Design & Analysis (10 credits)
• Effective Statistical Consultancy (10 credits)
• Medical Statistics (20 credits)
• Financial Econometrics (10 credits)
• Financial Stochastic Processes (10 credits)
• Data dashboards with RShiny (10 credits)
• Big Data Tools & Techniques (10 credits)
• Big Data Fundamentals (10 credits)
• Machine Learning for Data Analytics (20 credits)
• Statistical Machine Learning (10 credits)

Research Project

You'll undertake a research project in which you'll work on a real-life data set, putting the theoretical skills you have learned into practice.

Entry Requirements

• Academic requirements/experience: Minimum second-class (2:2) Honours degree or overseas equivalent. Mathematical training to A Level or equivalent standard. Prospective students with relevant experience or appropriate professional qualifications are also welcome to apply.
• Mathematical knowledge: Applicants are required to have some prior mathematical knowledge, eg A Level or equivalent in:
  • calculus
  • linear algebra
  • differential equations
• English language requirements: You must have an English language minimum score of IELTS 6.0 (with no component below 5.5).

Fees & Funding

All fees quoted are for full-time courses and per academic year unless stated otherwise.

• Scotland: £11,900
• England, Wales & Northern Ireland: £11,900
• Republic of Ireland: If you are an Irish citizen and have been ordinary resident in the Republic of Ireland for the three years prior to the relevant date, and will be coming to Scotland for Educational purposes only, you will meet the criteria of England, Wales & Northern Ireland fee status.
• International: £25,500

Careers

We work closely with the University's Careers Service. They offer advice and guidance on career planning and looking for and applying for jobs. In addition they administer and publicise graduate and work experience opportunities.

There are many exciting career opportunities for graduates in applied statistics. The practical, real-life skills that you'll gain means you'll be much in demand in international organisations. A report by the Association of the British Pharmaceutical Industry identified statistics and data mining as “two key areas in which a 'skills gap' is threatening the UK's biopharmaceutical industry.”

Graduates from the MSc Applied Statistics programme have gone on to be employed in a number of different sectors such as:

• Clinical Trials Statistician at Usher Institute
• Data Analyst at Bending Spoons
• Associate Statistician at Thermo Fisher Scientific
• Biostatistician at Optical Express
• Statistician at Phastar (x7)
• Statistician at Quotient Sciences (x3)
• Information Analyst at NHS Scotland
• Statistician at Scottish Government (x4)
• Statistician at Abbots Diabetes Care
• Medical Statistician at University of Oxford
• Credit Risk Analyst at Clydesdale Bank
• Statistical Analyst at Medpace
• Data Scientist at Scottish Water
• PhD studentship in social sciences

The course offered a wide variety of optional courses to choose from which would help to tailor my experience helping to become more specialised and prepare myself for many fields of industry.

Glenn McCreadie, Graduate

Teaching Staff

Staff member | Research Expertise
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Dr Neil Banas | An oceanographer and mathematical ecologist, with a background in physical oceanography. Current research investigating how climate change affects marine ecosystems and the role of biological complexity (diversity, adaptability, behaviour, life history) in large-scale patterns in the ocean.
Dr Bingzhang Chen | Current research is on how biodiversity affects marine ecosystem functioning such as primary production and biological carbon pump, for which the primary producers particularly phytoplankton play the pivotal role.
Dr Alison Gray | Research interests cover pattern recognition and machine learning, image analysis, applied epidemiology, SDE models for epidemics, and applications of statistics for honey bee research.
Prof David Greenhalgh | Research interests include mathematical and statistical techniques applied to biological problems, in particular mathematical and statistical modelling in epidemiology.
Dr Kim Kavanagh | Statistical expertise in the analysis and modelling of large observational health datasets with research interest in the fields of public health epidemiology, pharmacoepidemiology and digital health.
Dr Louise Kelly | Part-time Senior Risk Analyst Animal and Plant Health Agency (APHA) with research interests in veterinary and public health risk assessment and mathematical modelling projects relating to e.g. bovine tuberculosis, bovine brucellosis, foot and mouth disease, bluetongue, campylobacter, salmonella and rabies.
Prof Chris Robertson | Professor of Public Health Epidemiology in the Department of Mathematics and Statistics, and Head of Statistics at Public Health Scotland. Main research interest is in statistical modelling of infectious diseases and in epidemiological studies.
Dr David Young | Part-time Senior Consultant Statistician for NHS Scotland with research interests in design, conduct and analysis of medical research studies.
Dr Ainsley Miller | Teaching Associate with interests in mathematics and statistical pedagogy, in particular easing the transition from school to university and understanding the mental health struggles of students. Member of the core team of the Scottish Qualification Authority's Higher Applications of Mathematics course. Qualified Mental Health First Aider and Sexual Assault First Responder who runs a support service for all mathematics and statistics students.
Ryan Stewart | Teaching Associate with interest in statistical pedagogical research. Statistical expertise in the linkage and analysis of large administrative datasets in the field of public health epidemiology and policy. Member of Higher Education Academy.
Andrew Browne | Previous research experience includes analysis of data from clinical trials, observational studies, and systematic reviews. Teaching and pedagogical interests focus on the teaching of statistics to those from other disciplines.

The training is fast-paced, bringing students up to speed with the necessary practical skills in a very short time period. This means that our graduates are very attractive to government and industry.

Dr Louise Kelly, Postgraduate Taught Director, Department of Mathematics and Statistics

Pre-Masters Preparation Course

The Pre-Masters Programme is a preparation course held at the University of Strathclyde International Study Centre, for international students (non- UK/Ireland) who do not meet the academic entry requirements for a Masters degree at University of Strathclyde.

Upon successful completion, you'll be able to progress to this degree course at the University of Strathclyde.

Funding Opportunities

We've a large range of scholarships available to help you fund your studies. Check our scholarship search for more help with fees and funding.

International Students

We've a thriving international community with students coming here to study from over 140 countries across the world. Find out all you need to know about studying in Glasgow at Strathclyde and hear from students about their experiences.