(Full time) 2019 start
Statistics MSc
Overview
Statistics MSc 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 clinical trials 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. You’ll apply these skills in an independent research project.
Accreditation
This programme is accredited by the Royal Statistical 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. 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 allow you to specialise in the areas of statistics that interest you. Specialist areas within the course include biological or financial applications of statistics, or broad-based statistical expertise.
Want to find out more about your modules?
Take a look at the Statistics module descriptions for more detail on what you will study.
Course structure
The list shown below represents typical modules/components studied and may change from time to time. Read more in our Terms and conditions.
Modules
Year 1
Compulsory modules
- Independent Learning and Skills Project 15 credits
- Statistical Computing 15 credits
- Dissertation in Statistics 60 credits
Optional modules (selection of typical options shown below)
- Introduction to Clinical Trials 15 credits
- Introduction to Health Data Science 15 credits
- Further techniques in Health Data Analytics 15 credits
- Modelling Strategies for Causal Inference with Observational Data 15 credits
- Latent Variable Methods 15 credits
- Mathematical Biology 15 credits
- Evolutionary Modelling 15 credits
- Linear Regression and Robustness 15 credits
- Statistical Theory 15 credits
- Stochastic Calculus for Finance 15 credits
- Multivariate Analysis 10 credits
- Time Series 10 credits
- Bayesian Statistics 10 credits
- Generalised Linear Models 10 credits
- Discrete Time Finance 15 credits
- Continuous Time Finance 15 credits
- Risk Management 15 credits
- Advanced Mathematical Biology 20 credits
- Advanced Evolutionary Modelling 20 credits
- Linear Regression, 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
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.
Applying, fees and funding
Entry requirements
A bachelor degree with a 2:1 (hons) in a relevant subject.
We accept a range of international equivalent qualifications. For information please contact the School of Mathematics admissions team.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in all components. For other English qualifications, read English language equivalent qualifications.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks).
If you need to study for longer than 10 weeks, read more about our postgraduate pre-sessional English course.
How to apply
Application deadlines
31 July 2019 - International applicants
31 August 2019 - Home/EU applicants
This link takes you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.
Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.
Admissions policy
Faculty of Maths and Physical Sciences Postgraduate Admissions Policy 2019
Fees
- UK/EU: £10,000 (total)
- International: £21,000 (total)
Read more about paying fees and charges.
Visit our Brexit page for the latest information on the effect of the UK's exit from the EU on current students and applicants to the University.
For fees information for international taught postgraduate students, read Masters fees.
Additional cost information
There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more about additional costs
Scholarships and financial support
If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government. Find out more at Masters funding overview.
The School of Mathematics offers a range of scholarships for UK, EU and International students.
Find out more about our Scholarships.
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.