Occurrence of a Complementary Event in Probability-Learning

Abstract

Ss were trained to predict the occurrence of a single event as a function of the probabilities of this event following individual predictors (πs = .10, .30, .50, .70, .90). Half of the Ss were trained to make these predictions in a situation where a second event complementary to the first occurred whenever the first event did not occur and half made the predictions where the first event either occurred or did not occur and nothing else happened. Rather clear cut differential “learning” of the individual probabilities was demonstrated.