Encounters with big data: An introduction to using big data in the social sciences

This 4-day course run by the UK Data Service introduces key concepts and discussions around using big data in the social sciences, and introduces attendees to approaches to and open source tools for exploring and analysing big data. The course, aimed at experienced researchers, statisticians, or data analysts, covers aspects of data evaluation (ethical, legal and practical), extraction, exploration, basic analysis and visualisation of data from the web using Spark R and R. Participants then spend a day on group projects applying what they have learned on real data. The final afternoon looks at the challenges of replicability in science and shows how to set up a GitHub repository to document code, and best practices in being transparent about data and analysis when publishing results. This course focuses on quantitative data and will not cover in any detail text, social media, audio etc. This course is part of the IADS Big Data and Analytics Summer School.

Level: Introductory

Experience/knowledge required: Experience using quantitative research data in the social sciences. A good understanding of statistical methodology and concepts like standard error and standard deviation. Competence in writing commands in a statistical computing environment like Stata, R or SPSS.

Target audience: Aimed at experienced researchers, statisticians, or data manager