Revision of opinion with verbally and numerically expressed uncertainties

Abstract

Are verbal judgements of uncertainty more accurate and less conservative relative to the Bayesian calculations than are numerical judgements? This question was investigated by using a within-subject design in which subjects were required to estimate, numerically on some trials and verbally on others, the probability of one of two mutually exclusive hypotheses in a series of sequential probability revision tasks. The membership functions of the verbal phrases that were actually stated were assessed. Two alternative point values were used to represent these functions in a statistical comparison with the numerical probability judgements. The results show that verbal judgements are less conservative but more variable, and consequently less accurate, than numerical. The degree of conservatism and accuracy depends on the manner in which the membership function is converted to a point value.