The authors tested a model of category effects on stimulus judgment. The mo
del holds that the goal of stimulus judgment is to achieve high accuracy. F
or this reason, people place inexactly represented stimuli in the context o
f prior information, captured in categories, combining inexact fine-grain s
timulus values with prior (category) information. This process can be liken
ed to a Bayesian statistical procedure designed to maximize the average acc
uracy of estimation. If people follow the proposed procedure to maximize ac
curacy, their estimates should be affected by the distribution of instances
in a category. In the present experiments, participants reproduced one-dim
ensional stimuli. Different prior distributions were presented. The experim
ents verified that people's stimulus estimates are affected by variations i
n a prior distribution in such a manner as to increase the accuracy of thei
r stimulus reproductions.