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.
Sue Donnelly who is an LSE archivist wrote a wonderful piece on the Bowley portrait (below) and this can be found on the Arts pages and also on the LSE blog. Sue was very pleased to write this piece and she found it a fascinating story.
We offer three undergraduate honours degree courses: BSc Actuarial Science, BSc Business Mathematics and Statistics and BSc Financial Mathematics and Statistics. 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.
The MSc Statistics currently incorporates two separate streams. The MSc Statistics provides intensive training in statistics applicable to the social sciences, econometrics and finance; while the MSc Statistics (Financial Statistics) offers high-level training in statistics with applications in finance and econometrics.
2017-18 sees the introduction of our new stream called MSc Statistics (Social Statistics) which aims to provide high-level training in the theory and application of modern statistical methods, with a focus on methods commonly used in the social sciences. Each of these three programmes also offers a 12 month research option. This is similar to the above 9 month programmes, but involves a compulsory dissertation which replaces one unit’s worth of optional courses.
The MSc Quantitative Methods for Risk Management (formerly known as MSc Risk and Stochastics) offers in-depth instruction in probabilistic, statistical, and computational methods to quantify risk arising from, but not limited to, economic, financial, and insurance applications.
The MSc Data Science, being introduced in 2017/18, provides training in data science methods, with a focus on statistical perspectives. Students will receive a thorough grounding in theory, much of it at a high mathematical level, as well as gain practical skills of applied data science, enabling them to apply advanced methods of data science and statistics to investigate real world questions.
We welcome MPhil/PhD applications from students with an excellent MSc or equivalent qualification and an interest in time series analysis, stochastic modelling, financial mathematics, actuarial statistics, all areas of applied probability, latent variable modelling, analysis of longitudinal and clustered data, nonresponse and measurement error, sample survey methods, computational statistics, machine learning, distributed computing, and broad area of data science.