The theorem allows us to calculate the probability of a hypothesis H (you have the disease) being true, given evidence E (the test is positive). This is written as P(H|E): the probability of H given E. Bayes’s theorem says: Let’s unpack the various terms on the right-hand side of the equation. P(H): The probability that someone picked at random from the population has the disease. This is also called the prior probability (before taking any evidence into account). In our case, we can assume it is 1⁄1000, or 0.001, based on what’s been observed in the general population thus far.
