Bayes' Rule is a way of calculating conditional probabilities. It is difficult to find an explanation of its relevance that is both mathematically comprehensive and easily accessible to all readers. This article tries to fill that void, by laying out the nature of Bayes' Rule and its implications for clinicians in a way that assumes little or no background in probability theory. It builds on Meehl and Rosen's (1955) classic paper, by laying out algebraic proofs that they simply allude to, and by providing extremely simple and intuitively accessible examples of the concepts that they assumed their reader understood.
Keywords: Bayes theory; base rates; diagnosis; probability.