Hosted by the Alan Turing Institute
The steady expansion in the availability and reach of observational data has prompted much-needed introspection into data analysis practice. When using data to answer questions, it is not simply a case of choosing from a set of appropriate statistical procedures or "rolling out" some research design template. Effective data analysis requires analysts to make decisions within a wide space of analysis options and to engage deeply with the processes and mechanisms being represented through data. This public lecture features three internationally-standout scientists from academia and industry.
Talks will cover how to challenge and interrogate in data-based research, techniques for imagining uncertainty and variation in observational data, and how data-driven analyses can be put into production.