Statistics MSc

The MSc in Statistics is a flexible degree programme enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics.

The programme combines in-depth training in mainstream advanced statistical modelling with a broad range of specialisations - from financial mathematics to statistical bioinformatics; from shape analysis to risk management. You’ll also develop your understanding of research methods in statistics from writing styles to programming skills, preparing you for a wide range of careers in different sectors – and then apply them to a substantial research project of your own.

If you do not meet the full academic entry requirements then you may wish to consider the Graduate Diploma in Mathematics. This course is aimed at students who would like to study for a mathematics related MSc course but do not currently meet the entry requirements. Upon completion of the Graduate Diploma, students who meet the required performance level will be eligible for entry onto a number of related MSc courses, in the following academic year.

Accreditation

Royal statistical Society Accreditation

On graduation you will be eligible for the Graduate Statistician (GradStat) status and after five years’ experience this can be converted into the professional status of Chartered Statistician (CStat).

Being a chartered statistician provides employers, contractors and collaborators of statisticians a level of assurance that you are at the forefront of your field and is a mark of accomplishment to society.

Course content

The first two semesters of your course will consist of taught modules and in the third semester you will devote your time to a major dissertation.

Within each semester there is one compulsory module and a range of optional modules, allowing you to specialise in the area of statistics of most interest to you. Specialist areas within the course include biological or financial applications of statistics or broad based statistical expertise.The core modules will develop your skills to lay the groundwork of the programme. You’ll learn a range of statistical computing techniques and build research skills such as academic writing, programming and literature searches. Options within the course vary from mainstream topics in statistical methodology to more specialised areas and reflect specific research interests of our academic staff - examples include statistical shape analysis, directional data, statistical genetics and stochastic financial modelling.

Course structure

Compulsory modules

• Independent Learning and Skills Project 15 credits
• Statistical Computing 15 credits
• Dissertation in Statistics 60 credits

Optional modules

• Introduction to Clinical Trials 15 credits
• Core Epidemiology 15 credits
• Multilevel and Latent variable Modelling 15 credits
• Advanced Modelling Strategies 15 credits
• Advanced epidemiological techniques 15 credits
• Mathematical Biology 15 credits
• Linear Regression and Robustness 15 credits
• Statistical Theory 15 credits
• Stochastic Financial Modelling 15 credits
• Multivariate Analysis 10 credits
• Time Series 10 credits
• Bayesian Statistics 10 credits
• Generalised Linear Models 10 credits
• Introduction to Statistics and DNA 10 credits
• Discrete Time Finance 15 credits
• Continuous Time Finance 15 credits
• Risk Management 15 credits
• Advanced Mathematical Biology 20 credits
• Linear Regression and Robustness and Smoothing 20 credits
• Multivariate and Cluster Analysis 15 credits
• Time Series and Spectral Analysis 15 credits
• Bayesian Statistics and Causality 15 credits
• Generalised Linear and Additive Models 15 credits
• Statistics and DNA 15 credits

For more information on typical modules, read Statistics MSc in the course catalogue

Learning and teaching

Teaching is by lectures, tutorials, seminars and supervised research projects.

Assessment

The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester three project is assessed by a written dissertation and a short oral presentation.

Career opportunities

There is a shortage of well-qualified statisticians in the UK and other countries. Numeracy, in general, is an attribute keenly sought after by employers.

The emergence of data mining and analysis means that demand for statisticians is growing across a wide range of professions - actuarial, betting and gaming industries, charitable organisations, commercial, environmental, financial, forensic and police investigation, government, market research, medical and pharmaceutical organisations. The course is designed specifically to meet this demand.

Many statistical careers require people educated to masters degree level. This course is designed to build on existing mathematical skills and deepen knowledge of statistics in order for you to access a variety of professions or pursue further research as a PhD student.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.

Visit the Statistics MSc page on the University of Leeds website for more details!