Cause and Effect - Understanding Causation in Scientific Research

Explore the critical distinction between correlation and causation in this 31-minute talk by Peter Tennant, a fellow of the Alan Turing Institute. Delve into the importance of scientists confidently discussing causation and discover how "causal inference" methods are revolutionizing epidemiology. Examine the limitations of AI in making sensible assumptions about complex data. Gain valuable insights into the relevance of these concepts, particularly in light of the Covid-19 pandemic, despite the talk being recorded prior to the UK lockdown.

Cause & Effect