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.
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)
**WAITING LIST** 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)
**WAITING LIST** 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)
**LIMITED AVAILABILITY** 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)
**LIMITED AVAILABILITY** 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.