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The International Master’s in Statistical Data Science develops your practical, statistical and computing skills to prepare you for a professional career in statistics or as a solid basis for further research in the area.
The programme has been designed to provide a deep understanding of the modern statistical methods required to model and analyse data. You will benefit from a thorough grounding in the ideas underlying these methods and develop your skills in key areas such as practical data analysis and data modelling.
It has been accredited by the Royal Statistical Society (RSS) and equips aspiring professional statisticians with the skills they need for posts in industry, government, research and teaching. It also enables you to develop a range of transferable skills that are attractive to employers within the public and private sectors.
Students whose mathematical and statistical background is insufficient for direct entry on to the appropriate programme, may apply for this course. The first year of the programme gives you a strong background in statistics, including its mathematical aspects, equivalent to the Graduate Diploma in Statistics. This is followed by the MSc in Statistical Data Science.
The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.
The Statistics Group is forward-thinking, with varied research, and received consistently high rankings in the last two Research Assessment Exercises.
Statistical Data Science at Kent provides:
You are more than your grades
For 2021, in response to the challenges caused by Covid-19 we will consider applicants either holding or projected a 2:2. This response is part of our flexible approach to admissions whereby we consider each student and their personal circumstances. If you have any questions, please get in touch.
A second class honours degree (2.2 or above) or equivalent in an appropriate quantitative subject.
The University will consider applications from students offering a wide range of qualifications. Some typical requirements are listed below. Students offering alternative qualifications should contact us for further advice.
If you are an international student, visit our International Student website for further information about entry requirements for your country, including details of the International Foundation Programmes.
The University requires all non-native speakers of English to reach a minimum standard of proficiency in written and spoken English before beginning a postgraduate degree. Certain subjects require a higher level.
For detailed information see our English language requirements web pages.
Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways.
Duration: 2 years full-time
Linear algebra, analysis, regression and probability and inference are core topics for the first year of this two-year programme, which also includes a dissertation module. In the second year, stochastic models and processes, Bayesian statistics and the analysis of large data sets are among the range of topics explored.
The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.
The programme is assessed by coursework involving: complex theoretical questions, analysis of real-world data using appropriate computing packagse over a range of areas of application; written unseen examinations. In the second year, there is also a substantial dissertation.
This programme aims to:
You will gain knowledge and understanding of:
You develop intellectual skills in:
You gain subject-specific skills in:
You will gain the following transferable skills:
The 2021/22 annual tuition fees for this programme are:
For details of when and how to pay fees and charges, please see our Student Finance Guide.
For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.* If you are uncertain about your fee status please contact firstname.lastname@example.org.
The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.
Find out more about general additional costs that you may pay when studying at Kent.
Search our scholarships finder for possible funding opportunities. You may find it helpful to look at both:
In The Complete University Guide 2021, the University of Kent was ranked in the top 10 for research intensity. This is a measure of the proportion of staff involved in high-quality research in the university.
Please see the University League Tables 2021 for more information.
In the Research Excellence Framework (REF) 2014, research by the School of Mathematics, Statistics and Actuarial Science was ranked 25th in the UK for research power and 100% or our research was judged to be of international quality.
An impressive 92% of our research-active staff submitted to the REF and the School’s environment was judged to be conducive to supporting the development of world-leading research.
There has been research in the area of statistical ecology at Kent for many years. We are part of the National Centre for Statistical Ecology (NCSE), which was established in 2005. For details of the work of the NCSE, see www.ncse.org.uk
The research conducted in this area at Kent is mainly on Bayesian variable selection, Bayesian model fitting, Bayesian nonparametric methods, Markov chain Monte Carlo with applications.
Research is focused on statistical modelling and inference in biology and genetics with applications in complex disease studies. Over the past few decades, large amounts of complex data have been produced by high through-put biotechnologies. The grand challenges offered to statisticians include developing scalable statistical methods for extracting useful information from the data, modelling biological systems with the data, and fostering innovation in global health research.
This theme encompasses both theory and applications. Theory is involved with supervised and unsupervised learning, matrix factorisation, modelling of high-dimensional time series, differential privacy, deep learning and networks, shape analysis and statistics on manifolds, and neuroimaging. Applications in biology, industry, medicine and psychiatry. Often new computational methods are the key to analysing complex big data problems.
In order to describe the data, it is common in statistics to assume a specific probability model. Unfortunately, in many practical applications (for instance in economics, population genetics and social networks) it is not possible to identify a specific structure for the data. Nonparametric methods provide statistical tools for addressing inference in these situations.
At Kent there is particular interest in the use of nonparametric methods including quantile regression and Bayesian nonparametric approaches. Application areas include modelling of the business cycle and capacity utilisation, calculating sovereign credit ratings, modelling of stock return data, and predicting inflation.
Full details of staff research interests can be found on the School's website.
Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.
Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.
The taught programmes in Statistics and Statistics with Finance provide exemption from the professional examinations of the Royal Statistical Society and qualification for Graduate Statistician status.
Kent’s Computing Service central facility runs Windows. Within the School, postgraduate students can use a range of UNIX servers and workstations. Packages available include R, SAS, MATLAB, SPSS and MINITAB.
Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Annals of Statistics; Biometrics; Biometrika; Journal of Royal Society, Series B; Statistics and Computing. Details of recently published books can be found within our staff research interests.
All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.
Learn more about the applications process or begin your application by clicking on a link below.
Once started, you can save and return to your application at any time.