Department of Statistics at LSE has a distinguished history. Its roots can be traced back to the appointment of Sir Arthur Lyon Bowley, an alumnus of the University of Cambridge, at LSE in 1895. He was appointed Chair in Statistics in 1919, probably the first appointment of its kind in Britain.
Presidents of the Royal Statistical Society drawn from the Department of Statistics at LSE have been Arthur Lyon Bowley, Maurice Kendall, Roy D. G. Allen, Henry Wynn, Claus Moser, James Durbin and David J. Bartholomew.
The department has an international reputation for development of statistical methodology that has grown from its long history of active contributions to research and teaching in statistics for the social sciences.
We offer three undergraduate honours degree courses: BSc Actuarial Science, BSc Business Mathematics and Statistics and BSc Statistics with Finance. These courses enable students who have enjoyed maths at A-level to develop their skills in mathematics and statistics. BSc Actuarial Science can also lead to exemptions from the 100 series of the Institute of Actuaries examinations. Emphasis is given to areas with practical applications in commerce, insurance, finance and government.
Our taught MSc Statistics and MSc Statistics (Financial Statistics) offer specialist training in statistics applied to the social sciences, finance and econometrics. Our MSc Risk and Stochastics provides high-level training in probability theory and statistics for random processes with applications in the areas of insurance and finance and their interface. All three programmes can be taken as intensive full-time one year programmes or part-time over two years. We provide a thriving and co-operative research environment for research students.
We welcome MPhil/PhD applications from students with an excellent MSc qualification and an interest in time series analysis, stochastic modelling, financial mathematics, actuarial statistics, latent variable modelling, analysis of longitudinal and clustered data, nonresponse and measurement error and sample survey methods.