Courses

When I was looking for a way to advance my learning and to further develop my skill set, then LSE was really at the top of my list.

I have found the quality of the instruction to be really superb.

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The Methods Research Programme provides students and professionals with the knowledge and training in research methods and skills as used by top researchers in the field.

We offer courses across three areas of social science research methods:

One-week long courses:

Ethnographic Methods and Practice (Next available in 2018)
This introductory course covers ethnographic theory, methods and practice, with a particular focus on connections between traditional forms of ethnographic enquiry and emergent digital methodologies. 

Evidence Based Health Economics (21-25 August 2017)
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. 

Factor Models in Time Series with Applications in Macroeconomics and Finance
 (Next available in 2018)
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 (14-18August 2017)
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.

Statistical Methods in Risk Management (Next available in 2018)
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 (14-18 August 2017)
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 (21-25 August 2017)
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.

Two-week long courses:

Intermediate Econometrics (14-25 August 2017)
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 (14-25 August 2017)
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 (14-25 August 2017)
This is an introductory course in qualitative research methods, preparing students to design, carry out, report, read and evaluate qualitative research projects.

Real Analysis (14-25 August 2017 + online component prior to course start date)
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. 

Statistical Methods for Social Research using SPSS (14-25 August 2017)
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 (14-25 August 2017)
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.

Departments

All Methods Summer Programme courses are taught by world-class academics and draw on the expertise of Faculty from many LSE departments, including:

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 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.

 

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