Statistics (MSc)  Statistics (MSc) University College London ../webroot/files/Institutions/cover_photo/1563944035University-London-1.jpg

Statistical Science skills are powerful tools that play a valuable role in all pure and applied sciences as well as in finance, law and marketing. New and exciting opportunities in industry, medicine, government commerce or research await the graduate who has gained the quantitative skills training provided by this MSc. What and how will I learn? The programme uses a broad-based approach to statistics, providing up-to-date training in the major applications and an excellent balance between theory and application. It covers modern ideas in statistics including applied Bayesian Methods, generalised linear modelling and object-oriented statistical computing, together with a grounding in traditional statistical theory and methods. Degree Structure Students undertake courses to the value of 180 credits. The programme consists of a foundation course, four core courses (60 credits) four optional courses (60 credits) and a research dissertation (60 credits). A Postgraduate Diploma (120 credits, full-time one year, part-time two years) is offered. Core Modules Foundation Course (not credit bearing) Statistical Models and Data Analysis Statistical Design of Investigations Statistical Computing Applied Bayesian Methods Dissertationreport All MSc students undertake an independent research project, culminating in a dissertation of 10,000-12,000 words. Options Decision and Risk Stochastic Systems Forecasting Statistical Inference Medical Statistics 1 Medical Statistics 2 Stochastic Methods in Finance Factorial Experimentation Advanced Topics in Statistics Further details available on subject website: http:www.ucl.ac.ukStatsprospective_postgraduatesmsc.html The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. External organisations deliver technical lectures and seminars where possible. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15 minute presentation. Why should I study this degree at UCL? One of the strengths of Statistical Science at UCL is the breadth of expertise on offer the research interests of staff span the full range from foundations to applications, and make important original contributions to the development of statistical science. London provides an excellent environment in which to study statistical science, being the home of the Royal Statistical Society as well as a base for a large community of statisticians, both academic and non-academic. The Statistics MSc has been accredited by the Royal Statistical Society. Graduates will automatically be granted the Society s Graduate Statistician status on application to the Society. Your future career A number of previous graduates have entered professional employment across a broad range of industry sectors or have pursued further academic study. Examples of previous graduate destinations include: University of Oxford: Statistical Modeller Imperial College: PhD Financial Mathematics University of Cambridge: PhD Medical Statistics Esure: Corporate Analyst Eiger Capital: Quantitative Analyst Deloitte: Audit Department PWC: Audit Department KPMG: Accounting Lloyds TSB: Trainee Actuary Others have obtained positions at the British Antarctic Survey, NHS Transplant Unit, Office for National Statistics and the Civil and Aviation Authority. Entry Requirements A minimum of an upper second-class Bachelor s degree in a quantitative discipline from a UK university or an overseas qualification of an equivalent standard. Knowledge of mathematical methods and linear algebra at university level and familiarity with introductory probability and statistics is required. Relevant professional experience will also be taken into consideration. How to apply Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application

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