Base rate

In mathematics, base rate generally refers to the (base) class probabilities unconditioned on featural evidence, frequently also known as prior probabilities. For example, if it were the case that 1% of the public are "medical professionals" and 99% of the public are not "medical professionals," then the base rates in this case are 1% and 99%, respectively.

Naturally, in assessing the probability that a given individual is a member of a particular class, we must account for other information besides the base rate. In particular, we must account for featural evidence. For example, when we see a person wearing a white doctor's coat and stethoscope, and prescribing medication, we have evidence which may allow us to conclude that the probability of this particular individual being a "medical professional" is considerably greater than the category base rate of 1%.

The normative method for integrating base rates (prior probabilities) and featural evidence (likelihoods) is given by Bayes rule. A large number of psychological studies have examined a phenomenon called base-rate neglect in which category base rates are not integrated with featural evidence in the normative manner.