Bayes’ theorem is so cool because it allows you to make predictions based on observations.
It is often taught, however, as a kind of alphabet soup of symbols and weird language (‘prior and posterior probabilities’) so that even very smart people fail to get it…and certainly can’t apply it for themselves.
In this diagram, the whole idea is explained as simply as possible (click on the image below for a bigger version):
Patrick Andrews has a PhD in Mechanical Engineering from Heriot-Watt University and an MSc in Neuroscience from the University of Cambridge.
A former Chartered Engineer and Chartered Mathematician, Patrick has worked in management consultancies and high-tech startups, and in academia as a postdoc in Applied Mathematics at Cambridge and a maths lecturer at De Montfort University.
Patrick is the father of three delightful (but not uniformly mathematical!) daughters.