Degree Programmes


The Department of Statistics offers three undergraduate degrees: BSc Actuarial Science, BSc Business Mathematics and Statistics and BSc Financial Mathematics and Statistics. The Actuarial Science degree applies mathematical skills to a range of applied subjects and helps to solve important problems for insurance, government, commerce, industry and academic researchers. Recent graduates have gone on to work in the areas of insurance (life and general), as well as banking, finance and statistics. The Business Mathematics and Statistics degree is a quantitative programme with a strong business-related component. Our students receive a thorough grounding in mathematics and statistics, and can choose to specialize in a variety of fields such as economics, finance, information systems, accounting, or demography. BMS graduates are broadly employable, and recent graduates have gone on to work in the areas of insurance, banking, accounting, statistics, civil service, postgraduate studies and business consultancy. The Financial Mathematics and Statistics degree will provide students with competence in the application of mathematical and statistical techniques, and an understanding of the theory behind the techniques. Students will acquire a sound knowledge of the principles underlying applications of mathematics, probability and statistics, together with an understanding of fundamental aspects of finance and of programming techniques. They will have knowledge and understanding of computational aspects and techniques in mathematics, statistics and finance, with the ability to think in a critical manner and the ability to make formal and informal inferences on the basis of statistical data.

The BSc Statistics with Finance course is no longer being recruited to and its last admission to new students was September 2016. It has been replaced by the new course BSc Financial Mathematics and Statistics which starts in 2017/18. If you are a prospective student, please note that BSc Statistics with Finance is no longer a course that you can apply for via UCAS. Here you can find information on the BSc Statistics with Finance course, but please note that this page is for current students as a reference only.


There are three taught MSc programmes.

The MSc Statistics incorporates two separate streams: MSc Statistics and MSc Statistics (Financial Statistics). From 2017/18 the third stream will be introduced, MSc in Statistics (Social Statistics).

MSc Statistics provides an excellent grounding for employment in the private or public sectors in Statistics, related quantitative fields or for academic research. The proof of the growing need for statistical modelling in many fields is the very strong career opportunities for our MSc graduates. Focusing on statistical methodology and its interface with economics, finance and social science, the MSc has an emphasis on the most successful statistical methods as well as cutting-edge new developments offering hands-on experience in real data analysis using the R Package.

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. This programme is LSE’s timely response to industry’s strong demand in experts with quantitative expertise in risk management, finance, insurance, and their interface.I

The MSc Data Science, being introduced in 2017/18, provides training in data science methods, with a focus on statistical perspectives. You 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 you to apply advanced methods of data science and statistics to investigate real world questions. 


The Department of Statistics also offers opportunities for doctoral research(MPhil/PhD) within our three main research groups, as well as in the Centre for the Analysis of Time Series (CATS). A dedicated Research Students section can be accessed here.

Teaching environment

In support of all students studying within the Department of Statistics, there is a dedicated administrative team that can be found on the 6th floor of Columbia House. Office opening times are from 10:00-13:00 and 14:00-16:00 Monday to Friday in COL.6.11. In addition, each programme of study is run by an academic member of staff acting as Course Tutor (BSc) or Programme Director (MSc and MPhil/PhD). Course Tutors and Programme Directors oversee all aspects of the academic management of courses offered by the department. Details of all Staff and research students in the Department of Statistics can be found on the Who's Who pages.

Useful contacts


Head of Department: Professor Pauline Barrieu
Deputy Heads of Department: Professor Irini Moustaki  and Dr Erik Baurdoux

BSc Actuarial Science Course Tutors: Dr Luciano Campi and Dr Angelos Dassios
BSc Business, Mathematics & Statistics and BSc Statistics with Finance Course Tutor: Dr Wicher Bergsma 

MSc Statistics Programme Director: Professor Fiona Steele
MSc Statistics (Financial Statistics) Programme Director: Dr Yining Chen
MSc in Statistics (Social Statistics) Programme Director: Professor Fiona Steele *
MSc Risk & Stochastics Programme Director: Dr Hao Xing
MSc in Data Science Programme Director: Professor Milan Vojnovic *

* These two programmes are introduced in 2017/18.

Doctoral Research Programme Director: Dr Angelos Dassios


Departmental Manager: Imelda Noble
Undergraduate Administrator: Steve Ellis
MSc Administrator: Sarah McManus
Research Administrator: Penny Montague
Events and Communications Officer: Penelope Smith

Examination Sub-Board Chairs

BSc Actuarial Science: Dr Angelos Dassios
BSc Business, Mathematics & Statistics and BSc Statistics with Finance: Dr Kostas Kalogeropoulos
MSc Statistics and MSc Statistics (Financial Statistics): Professor Fiona Steele and Dr Yining Chen
MSc Risk & Stochastics ( to be re-named to MSc Quantitative Methods in Risk Management from 2017/18 onwards): Dr Hao Xing

Other useful information

On joining the School, undergraduate students will be assigned a member of academic staff within the Department of Statistics as an Academic Adviser who will offer guidance on course options, finances and life at university. A full list of Academic Advisers for the current academic year can be accessed via the course homepage on Moodle. For MSc students this role is taken on by the Programme Director. Similarly, research students are allocated first and second year supervisors who are both responsible for offering academic guidance and advice, along with helping with more practical queries and concerns.

Students also have the opportunity to raise concerns about any issue they are facing through the Staff Student Liaison Committee (SSLC). This committee provides a forum within which academic staff and students can raise and discuss issues relating to: teaching within the department; the content and design of courses; departmental administration; and the facilities provided by the department and the School. There is a separate committee for each undergraduate degree programme and taught Masters, as well as one for the department's MPhil/PhD programme. Please click here for the latest SSLC guidance for chairs and members.

Meet our Excellence in Education Award Winners, October 2016


Professor Pauline Barrieu (Risk and Stochastics group)
Professor Irini Moustaki (Social Statistics group)
Professor Fiona Steele (Social Statistics group)
Dr Hao Xing (Risk and Stochastics group) 

LSE’s Excellence in Education Awards are made to staff who have demonstrated outstanding teaching contribution and educational leadership in their departments.

Professor Irini Moustaki talks about her approach to teaching.

My favourite thing about teaching at LSE is the students

What makes being a statistician within a social science institution like LSE so enjoyable is that we get students from very different academic backgrounds who are all extremely motivated.

The courses I teach include students from Statistics, Social Policy, Government, Social Psychology, and others from across the School. What I like most is that they all ask very different questions - from a focus on mathematics, to what concepts mean, to how they can use methods in real data problems.

I tell students that statistics is like art

Statistics is not rigid. There are so many different ways of approaching the subject and it’s not something that you can only learn from your text book. Whenever you have to explore a research question, creativity and knowledge of different statistical areas are required.

Often in the beginning, students think there is just one solution for every problem, so it’s intriguing when they realise that for any statistical problem there is more than one way forward, and there are always pros and cons to each option.

I like putting students’ minds at ease about statistics

Sometimes the subject can be a bit intimidating, but I always try to find ways to show that statistics can be done in an easy and enjoyable way.

What’s so special about LSE is that teaching and research are so intertwined

My research is about developing methods and tools for measuring behaviour and attitudes, and the fact I can teach courses that are related to the techniques I’ve been learning and developing throughout my academic career is something that I really value.

At LSE we like people to teach things that are connected to their research, but teaching is also an opportunity to connect with students and help them to develop their own interests and ideas. In that way you can be a good researcher, but you need to be a good teacher as well.

I find students’ enthusiasm inspiring

Our students are highly engaged. It’s great when different points of view coincide in class and when students from different subjects learn from each other.

I also like that our students ask questions, and are willing to follow things up with you. Social science students want to understand methods and tools to solve their own data problems, and sometimes in class you get questions that you don’t know the answer to that leads to a new problem to think about. In that way, my research inspires my teaching and my teaching inspires my research.

I bring a lot of humour into teaching

I try to make students feel relaxed and encourage discussion. I also provide resources prior to class for students to work on. I am keen to keep developing and enhancing my teaching skills by observing other lectures and attending teaching events organised by the teaching and learning centre.

I also encourage my students to go to seminars and listen to other people’s ideas and areas of work – it helps you realise that there’s another world out there that you have to step into and explore yourself.

My advice to anyone who is just starting to teach is to be compassionate to students

I was a PhD student at LSE, and when I first started teaching I learnt that you have to be very understanding. It’s important to bring humanity into the classroom, and encourage students to help and learn from each other.