The course will involve four sessions:

1. Introductory material will explain the growing significance of big data; importance of analytics including modelling and simulation; protocols and standards for data management; need for a spatial perspective; the relevance of policy, impact and external interactions
2. The current status and recent changes in the data landscape will be reviewed, including an overview of ESRC investments and discussion of new types of data which are now becoming available. There will be some discussion of the similarities and differences between big data sources and conventional surveys and databases?
3. The course will include a collaborative hands-on session to explore potential relevance and interpretation of big data for the projects which are of interest to individual student participants
4. Practical case studies will be used to illustrate methods and challenges. A mini ‘hackfest’ will be established using real data to evaluate preliminary conclusions for indicative applied problem(s)

Target audience is social science PhD students whose work includes a significant interest in quantitative methods, and whose current, previous, and/or intended research includes significant secondary analysis of large datasets. The course will include fragments of coding and analysis in both R and Excel, but previous experience will not be assumed in either case.

The training will introduce new concepts in big data and will depend on an appreciation of challenges relating to inference, hypothesis generation, statistical analysis, mathematical modelling. Although detailed prior knowledge of one or more of these areas is not essential, a broad knowledge of issues surrounding the use of data in social science research will be assumed.

We will use large data sets from the ESRC Consumer Data Research Centre including small area income profiles (from Acxiom Ltd), diet and nutrition (UK Women’s Cohort Study), cycling/ urban transport (e.g. DfT) and consumer lifestyles (Call Credit).

For further information, please contact Eleri Pound.