The course will involve four sessions:
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.