We offer courses across three areas of social science research methods:
Click above on your area of interest. Alternatively, a full list of courses can be found below.
Applied Health Econometrics (22-26 August 2016)
Gain an in-depth overview into the application of econometric techniques to health economics. The focus is on producing i) good descriptive analysis and ii) casual inference. The entire course is lab-based and mixes computer exercises with traditional lectures
Ethnographic Methods and Practice
**This course will next take place in 2017**
During this intensive one-week course, students will learn how to design and conduct ethnographic fieldwork, integrate ethnography into mixed-methods designs and analyse ethnographic data.
Factor Models in Time Series with Applications in Macroeconomics and Finance (22-26 August 2016)
A graduate level course about “big data” analysis. It introduces methods and techniques for extracting meaningful and useful information from large panels of time series.
Latent Variable Modelling and Structural Equation Modelling for Social Sciences Research (15-19 August 2016)
A course on latent variables and structural equation models for continuous and categorical observed variables for cross-sectional and longitudinal data, and their applications to social sciences.
Research Methods for the Online World (22-26 August 2016)
This course explores the opportunities and challenges of online data collection and analysis, from online surveys and web experiments to social data and opinion mining, social networks and other digital methods.
Statistical Methods in Risk Management (15-19 August 2016)
A self-contained introduction to statistical methods in risk management. This course combines theory and implementation, and emphasises on hands-on experience working with real financial data.
Tools for Macroeconomists: The Essentials (15-19 August 2016)
A hands-on graduate-level course teaching key techniques to solve, analyse, and estimate macroeconomic models. It teaches the key building blocks of numerical analysis and shows how to use them to solve dynamic stocastic models.
Tools for Macroeconomists: Advanced Tools (22-26 August 2016)
Offering a higher level of understanding in the state-of-the-art techniques used to solve and analyse advanced macroeconomic models. In particular, models with heterogeneous agents and models with inequality constraints.
Intermediate Econometrics (15-26 August 2016)
This course aims to build a solid, comprehensive understanding of the use of the regression model when one progresses from the Classical Linear Regression Model, with its strong and unrealistic assumptions, and addresses the issues that researchers encounter in practice.
Introduction to Data Science and Big Data Analytics (15-26 August 2016)
This programme covers the fundamentals of data science, focusing on predictive analytics and extracting patterns from big data. Topics include statistical methods, data structures and data manipulation. Technologies used include R for analytics and introductory usage of SQL for database management.
Qualitative Research Methods (15-26 August 2016)
This is an introductory course in qualitative research methods, preparing students to design, carry out, report, read and evaluate qualitative research projects.
Real Analysis (8-26 August 2016)
A considerable part of economic theory is difficult to follow without a strong background in real analysis. This course will introduce students to concepts of modern analysis such as continuity, metric spaces, compactness and convexity, and will show the connections to economic theory. Note: this course has a week-long online component prior to the start of the two-week on-campus component.
Statistical Methods for Social Research using SPSS (15-26 August 2016)
Data-driven research requires knowledge of the appropriateness of different statistical techniques and the means to perform empirical calculations. This course equips researchers with these tools using the popular SPSS package.
Survey Research Methods: From Design to Analysis (15-26 August 2016)
This course provides a comprehensive understanding of survey research methods, including how to design surveys, how to analyse different types of survey data, and how to critically evaluate survey-based research.
Department of Economics
LSE’s Department of Economics is one of the largest in the world. It has an outstanding international reputation based on its research and publications and is acknowledged as the leading faculty in Europe. The department is consistently ranked in the top 20 economics departments worldwide, and has produced a number of Nobel laureates, including Professor Chris Pissarides, the joint winner of the 2010 Nobel Prize in Economics.
Department of Mathematics
The LSE Mathematics Department is internationally recognised for its teaching and research. Located within a world-class social science institution, the department aims to be a leading centre for mathematics in the social sciences.
Department of Methodology
The Department of Methodology was set up at LSE to coordinate and provide a focus for methodological activities at the School, in particular in the areas of research student training and of methodological research. The department is heavily involved in the School-wide Master's programme in Social Research Methods, and provides courses for research students from all parts of the School, with the aim of making LSE the pre-eminent centre for methodological training in the social sciences.
Department of Social Policy
The Department of Social Policy is the longest established in the UK and has received the highest possible rating in all Research Assessment Exercises carried out in the UK. In the last RAE in 2008 it led the field nationally with 50 per cent of its research recognised as world-leading, and 100 per cent ranked at international level.
Department of Sociology
The Department of Sociology at LSE was the first to be established in Britain and has played a key role in establishing and developing the discipline - nationally and internationally - since 1904.
Department of Statistics
The Department of Statistics at LSE 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.
All courses are full time, and will generally involve 3 hours of lectures and 1.5 hours of classes per day, though teaching format varies from course to course. Classes provide an opportunity for group discussions, a chance to work through problem sets and training in relevant software packages. Any software required will be available for use on the LSE network.
Assessment for most courses will be in the form of a 2-hour written examination on the last day of the course. Some courses may also involve some coursework during the programme. Whilst the examination is not compulsory, it is encouraged. Students who do not sit the examination will be entitled to an attendance certificate provided they have attended 80% of all classes.
Certificates and Transcripts
On completion of the programme, a certificate and transcript will be provided. Students who complete all graded assessment (including the final exam) will receive an overall final grade which is shown on the certificate and transcript.
In the case of partial or non-completion of the graded assessment, an attendance certificate will be provided, though 80% of all classes must have been attended.