This EA Student Summit 2020 talk is a friendly introduction to the formal model of learning from new evidence called "Bayesian updating". The Bayesian rule for updating is the most general account of how evidence works, encompassing and explaining the (limited) usefulness of statistical ideas like p-values and confidence intervals. This talk will show you how to do Bayesian updating in your head, using a simple formulation equivalent to the much more unwieldy equation known as 'Bayes' theorem.'

In the future, we may post a transcript for this talk, but we haven't created one yet. If you'd like to create a transcript for this talk, contact Aaron Gertler — he can help you get started.