Learning conditional frequencies in a probability learning task

Abstract The study was prompted by a theoretical discussion of probability learning by Estes (1976). In three separate experiments, subjects were presented with frequency information in the form of wins and losses among 3 teams, and later predicted future wins and losses. Frequencies were devised so that conditional win frequencies for a pair of teams were either inconsistent or consistent with marginal win frequencies for each team. In experiment 1, when subjects predicted future events on the basis of known past frequencies, predictions were generally based on conditional frequencies. In experiment 2 six blocks of observations were presented, with predictions following each block. What little learning did occur was in the direction of the conditional frequencies. Subjects in experiment 3 were able to learn conditional frequencies when given explicit instructions to do so. Results were discussed in terms of a two-stage hypothesis generation model that might operate within the framework of an associative theory of probability learning.