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.
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.
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.
Teaching is by lectures, tutorials, seminars and supervised research projects.
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.
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.
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.
Research in the Division of Genetics and Genomics aims to advance understanding of complex animal systems and the development of improved predictive models through the application of numerical and computational approaches in the analysis, interpretation, modelling and prediction of complex animal systems from the level of the DNA and other molecules, through cellular and gene networks, tissues and organs to whole organisms and interacting populations of organisms.
The biology and traits of interest include: growth and development, body composition, feed efficiency, reproductive performance, responses to infectious disease and inherited diseases.
Research encompasses basic research in bioscience and mathematical biology and strategic research to address grand challenges, e.g. food security.
Research is focussed on, but not restricted to, target species of agricultural importance including cattle, pigs, poultry, sheep; farmed fish such as salmon; and companion animals. The availability of genome sequences and the associated genomics toolkits enable genetics research in these species.
Expertise includes genetics (molecular, quantitative), physiology (neuroendocrinology, immunology), ‘omics (genomics, functional genomics) with particular strengths in mathematical biology (quantitative genetics, epidemiology, bioinformatics, modelling).
The Division has 18 Group Leaders and 4 career track fellows who supervise over 30 postgraduate students.
Studentships are of 3 or 4 years duration and students will be expected to complete a novel piece of research which will advance our understanding of the field. To help them in this goal, students will be assigned a principal and assistant supervisor, both of whom will be active scientists at the Institute. Student progress is monitored in accordance with School Postgraduate (PG) regulations by a PhD thesis committee (which includes an independent external assessor and chair). There is also dedicated secretarial support to assist these committees and the students with regard to University and Institute matters.
All student matters are overseen by the Schools PG studies committee. The Roslin Institute also has a local PG committee and will provide advice and support to students when requested. An active staff:student liaison committee and a social committee, which is headed by our postgraduate liaison officer, provide additional support.
Students are expected to attend a number of generic training courses offered by the Transkills Programme of the University and to participate in regular seminars and laboratory progress meetings. All students will also be expected to present their data at national and international meetings throughout their period of study.
In 2011 The Roslin Institute moved to a new state-of-the-art building on the University of Edinburgh's veterinary campus at Easter Bush. Our facilities include: rodent, bird and livestock animal units and associated lab areas; comprehensive bioinformatic and genomic capability; a range of bioimaging facilities; extensive molecular biology and cell biology labs; café and auditorium where we regularly host workshops and invited speakers.
The University's genomics facility Edinburgh Genomics is closely associated with the Division of Genetics and Genomics and provides access to the latest genomics technologies, including next-generation sequencing, SNP genotyping and microarray platforms (genomics.ed.ac.uk).
In addition to the Edinburgh Compute and Data Facility’s high performance computing resources, The Roslin Institute has two compute farms, including one with 256 GB of RAM, which enable the analysis of complex ‘omics data sets.