When is p=.90 preferred to p=.70? preference for definitive predictions by lay consumers of probability judgments

What do people regard as an informative and valuable probability statement? This article reports four experiments that show participants to have a clear preference for more extreme and higher probabilities over less extreme and lower ones. This pattern emerged in Experiment 1, inwhich no context was provided, and was further explored in Experiment 2 within a positive and a negative context. The findings were further confirmed in Experiment 3, which employed a Bayesian framework with revisions of opinions. Finally, Experiment 4 showed how preference for high probabilities can lead people to prefer an overconfident to a more well-calibrated(accurate) forecaster. The results are interpreted as manifestations of a search for definitive predictions principle, which asserts that high probabilities are preferred to medium ones and often favored over the corresponding complementary low probabilities on the basis of their capacity to predict the occurrence of single outcomes

Waiting for the bus : when base rates refuse to be neglected

The paper reports the results from 16 versions of a simple probability estimation task, where probability estimates derived from base-rate information have to be modified by case knowledge. In the bus problem [adapted from Falk, R., Lipson, A., & Konold, C. (1994). The ups and downs of the hope function in a fruitless search. In G. Wright & P. Ayton (Eds.), Subjective probability (pp. 353–377). Chichester, UK: Wiley], a passenger waits for a bus that departs before schedule in 10% of the cases, and is more than 10 min delayed in another 10%. What are Fred’s chances of catching the bus on a day when he arrives on time and waits for 10 min? Most respondents think his probability is 10%, or 90%, instead of 50%, which is the correct answer. The experiments demonstrate the difficulties people have in replacing the original three-category 1/8/1 partitioning with a normalized, binary partitioning, where the middle category is discarded. In contrast with typical studies of "base-rate neglect", or under-weighing of base-rates, this task demonstrates a reversed base-rate fallacy, where frequentistic information is overextended and case information ignored. Possible explanations for this robust phenomenon are briefly discussed

(Yet) another look at the heuristics and biases research program

no abstract

The probability outcome correpondence principle : a dispositional view of the interpretation of probability statements

This article presents a framework for lay people's internal representations of probabilities, which supposedly reflect the strength of underlying dispositions, or propensities, associated with the predicted event. From this framework, we derive the probability-outcome correspondence principle, which asserts that strong dispositions should lead to (1) strong (forceful) and (2) immediate outcomes and, hence, be characterized by high probabilities. In contrast, weak dispositions lead to (1) weak (fragile) and (2) delayed outcomes and are thus associated with low probabilities. We describe six experiments designed to test the correspondence principle. In the final discussion, we examine the implications of the proposed framework, from both a normative and a descriptive viewpoint