Mathematics and Statistics

Statistics is data analysis. New kinds of data are emerging all the time in science and industry. Statisticians are needed to set up cutting edge statistical methods to analyse these data. Statistical methods use advanced mathematical ideas and modern computational techniques. They require expert knowledge and experience to apply. Statisticians do the work. This combination, of deep and mathematically well-grounded method-building, and wide-ranging applied work with data, is what makes statistics a great subject.

The Department of Statistics is the top-ranked Statistics department in the UK according to the Government’s 2008 Research Assessment Exercise. Many of its 27 academic staff work in the development of fundamental statistical methodology and probability. There is a large research group working on models and inference in genetics and evolution and their applications, for example concerning human genetic variation and disease. Other groups work on pattern recognition and image analysis, networks, medical, actuarial and financial applications. These interests are reflected in the lecture courses available to undergraduates in their third and fourth years.

Many of our graduates have careers in statistics and the closely related field of operational research. They are in demand in the insurance and financial services professions, especially those whose studies have included a substantial component of statistics and applied probability. In recent years about 35% of Oxford Mathematics graduates have joined the finance and finance-related sectors, and include a management analyst for a management consultancy firm and an actuarial consultant.

Ellis, who graduated in 2008, is now a strategist for Macquarie Capital Securities Limited. He says: ‘I have been working as a strategist in Hong Kong since June 2008 where I am involved in equity index sales, portfolio trading and trading models. The invaluable educational background from my degree gives a fair justification for my strong analytical and quantitative skills.’

Students interested in this course might also like to consider other Mathematics courses or Computer Science.