MSc Statistics (Social Statistics) (Research)

The MSc Statistics (Social Statistics) (Research) 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.

You'll gain insights into the design and analysis of social science studies, including large and complex datasets, study the latest developments in statistics, and learn how to apply advanced methods to investigate social science questions.

The programme includes two core courses which provide training in fundamental aspects of probability and statistical theory and methods, the theory and application of generalised linear models, and programming and data analysis using the R package. These courses together provide the foundations for the optional courses on more advanced statistical modelling, computational research and statistical computing. Options also include specialist courses from the Departments of Methodology, Geography and Social Policy. You'll also complete a dissertation on an approved topic of your choice.

The research stream is similar to the MSc Statistics (Social Statistics) nine-month programme but involves a compulsory dissertation which replaces one unit's worth of optional courses and extends the length of the programme to 12 months.

• R J Larsen and M L Marx Introduction to Mathematical Statistics and Its Applications (5th edition, Pearson, 2012)
• W N Venables, D M Smith and the R Core Team An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics (2016)

You'll take two compulsory courses, and will choose between three options. In addition, you'll take courses to the value of two units from an approved list of options.

The Department of Statistics at LSE is one of the oldest and most distinguished in the UK.

The department has an international reputation for the development of statistical methodology and a long history of pioneering contributions to research and teaching. Many of the world’s most famous and innovative statisticians have been associated with LSE.

Our research spans four main areas – data science, probability in finance and insurance, social statistics, and time series and statistical learning. The department has close links with the Data Science Institute at LSE – an interdisciplinary institute that fosters the study of data science, with a particular emphasis on the social, economic and political contexts.

All aspects of our research were ranked world-leading or internationally excellent in the most recent Research Excellence Framework (2021), submitted jointly with the Department of Mathematics.

The department’s research strengths are reflected in our teaching curriculum. We have a comprehensive range of undergraduate and postgraduate degrees and doctoral research opportunities – hosted in a vibrant department with a supportive and friendly community of staff and students.

Our alumni enjoy successful careers in diverse areas, such as banking, accounting, finance, statistics, government and business consulting while others pursue postgraduate study or research. Our alumni frequently return to LSE to share their career experiences with current students.

Learn more about our programmes and research.

Department of Statistics

We welcome applications from all suitably qualified prospective students. At LSE, we want to recruit students with the best academic merit, potential and motivation, irrespective of background.

We carefully consider each application and take into account all the information included on your application form, such as your:

• academic achievement (including predicted and achieved grades)
• statement of academic purpose
• two academic references
• CV.

See further information on supporting documents.

You may need to provide evidence of your English language proficiency. See our English language requirements.

Personal statement requirements

Your statement should explain why you're pursuing your selected programme and why you've chosen LSE's Department of Statistics. Brief details of your academic background and aspirations are also useful. If your background is outside of mathematics or statistics then you should provide further explanation of how your experience is relevant to the programme applied for.

Your personal statement should be concise and should not exceed 1,000 words.

If you're applying for more than one choice in the Department of Statistics, it's recommended that you submit two separate personal statements. If the two programmes for which you're applying are very similar and you would prefer to combine the information in one statement then you may do so; however, please ensure that your statement clearly addresses your motivations for applying for each separate programme.

1+3 scheme

This programme is available as part of an ESRC-funded pathway onto a PhD programme. The 1+3 scheme provides funding for a one year research training master's linked to a PhD programme and is designed for students who haven't already completed an ESRC recognised programme of research training. An application must be submitted for the relevant master’s programme, including a research proposal for the PhD aspect of the pathway. Applicants must also indicate their wish to be considered for the 1+3 pathway within their personal statement.

Please note: The applications, intake and ratio values below include the MSc Statistics (Social Statistics).

Applications for this programme are considered on a rolling basis. This means that applications will close once the programme is full.

There is no fixed deadline. However, if you’d like to be considered for any funding opportunities, you must submit your application (and all supporting documents) by the funding deadline. See the fees and funding section below for more details.

For this programme, the tuition fee is different for home and overseas students depending on their fee status.

For this programme, the tuition fee is different for home and overseas students depending on their fee status.

All taught courses include formative coursework which is unassessed. It's designed to help prepare you for summative assessment which counts towards the course mark and to the degree award. LSE uses a range of formative assessment, such as essays, problem sets, case studies, reports, quizzes, mock exams and many others. Most courses are summatively assessed by a two-hour exam in the Spring Term, although some contain an element of course work.

An indication of the formative coursework and summative assessment for each course can be found in the relevant course guide.

There is a high demand for graduates with advanced statistics training and an interest in social science applications, and students on this programme have excellent career prospects.

Potential employers include the public sector (the Office for National Statistics, government departments, universities), market research organisations, survey research organisations and NGOs. This programme would be ideal preparation for doctoral research in social statistics or quantitative social science.

Further information on graduate destinations for this programme

From CV workshops through to careers fairs, LSE offers lots of information and support to help you make that all-important step from education into work.

Many of the UK’s top employers give careers presentations at the School during the year and there are numerous workshops covering topics such as job hunting, managing interviews, writing a cover letter and using LinkedIn.

See LSE Careers for further details.