Seeing the Forest When Entry is Unlikely: Probability and the Mental Representation of Events (original) (raw)
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Journal of Experimental Social Psychology, 2008
Probability judgment is description-dependent; different descriptions of the same event can elicit different judged probabilities. We propose that the temporal proximity of an event moderates the degree of description dependence in probability judgment. According to construal level theory, near future events are represented more concretely than distant future events. These more concrete representations are predicted to be more stable, and therefore less susceptible to description dependence effects. Consistent with this prediction, changing an event's description by unpacking it into constituent parts influenced its judged probability more when the event took place in the distant rather than the near future. Specifically, greater description dependence was found for distant events regardless of whether the unpacking manipulation increased (Experiment 1) or decreased (Experiment 2) judged probability.
Organizational Behavior and Human Decision Processes, 2013
ABSTRACT Low numerical probabilities tend to be directionally ambiguous, meaning they can be interpreted either positively, suggesting the occurrence of the target event, or negatively, suggesting its non-occurrence. High numerical probabilities, however, are typically interpreted positively. We argue that the greater directional ambiguity of low numerical probabilities may make them more susceptible than high probabilities to contextual influences. Results from five experiments supported this premise, with perceived base rate affecting the interpretation of an event’s numerical posterior probability more when it was low than high. The effect is consistent with a confirmatory hypothesis testing process, with the relevant perceived base rate suggesting the directional hypothesis which people then test in a confirmatory manner.
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In recent studies of humans estimating non-stationary probabilities, estimates appear to be unbiased on average, across the full range of probability values to be estimated. This finding is surprising given that experiments measuring probability estimation in other contexts have often identified conservatism: individuals tend to overestimate low probability events and underestimate high probability events. In other contexts, repulsive biases have also been documented, with individuals producing judgments that tend toward extreme values instead. Using extensive data from a probability estimation task that produces unbiased performance on average, we find substantial biases at the individual level; we document the coexistence of both conservative and repulsive biases in the same experimental context. Individual biases persist despite extensive experience with the task, and are also correlated with other behavioral differences, such as individual variation in response speed and adjustment rates. We conclude that the rich computational demands of our task give rise to a variety of behavioral patterns, and that the apparent unbiasedness of the pooled data is an artifact of the aggregation of heterogeneous biases.
Psychological Review, 2014
We present a computational model to explain the results from experiments in which subjects estimate the hidden probability parameter of a stepwise nonstationary Bernoulli process outcome by outcome. The model captures the following results qualitatively and quantitatively, with only 2 free parameters: (a) Subjects do not update their estimate after each outcome; they step from one estimate to another at irregular intervals. (b) The joint distribution of step widths and heights cannot be explained on the assumption that a threshold amount of change must be exceeded in order for them to indicate a change in their perception. (c) The mapping of observed probability to the median perceived probability is the identity function over the full range of probabilities. (d) Precision (how close estimates are to the best possible estimate) is good and constant over the full range. (e) Subjects quickly detect substantial changes in the hidden probability parameter. (f) The perceived probability sometimes changes dramatically from one observation to the next. (g) Subjects sometimes have second thoughts about a previous change perception, after observing further outcomes. (h) The frequency with which they perceive changes moves in the direction of the true frequency over sessions. (Explaining this finding requires 2 additional parametric assumptions.) The model treats the perception of the current probability as a by-product of the construction of a compact encoding of the experienced sequence in terms of its change points. It illustrates the why and the how of intermittent Bayesian belief updating and retrospective revision in simple perception. It suggests a reinterpretation of findings in the recent literature on the neurobiology of decision making.
Where do probability judgments come from? Evidence for similarity–graded probability
2001
This paper compares four models of the processes and representations in probability judgment. The models represent three principles that have been proposed in the literature: 1) the representativeness heuristic (interpreted as relative likelihood or prototype-similarity), 2) cuebased relative frequency, and 3) similarity-graded probability. An experiment examined if these models account for the probability judgments in a category learning task. The results indicated superior overall fit for similaritygraded probability throughout training. In the final block, all models except similarity-graded probability were refuted by data.
Memory & Cognition, 2001
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.
A review of human linguistic probability processing: General principles and empirical evidence
Knowledge Engineering Review, 1995
This article reviews research on how people use and understand linguistic expressions of uncertainty, with a view toward the needs of researchers and others interested in artificial intelligence systems . We discuss and present empirical results within an inductively developed theoretical framework consisting of two background assumptions and six principles describing the underlying cognitive processes .
Journal of Experimental Psychology-human Perception and Performance, 1990
Previous research has demonstrated substantial effects of context on the numerical interpretation of verbal probability statements and has attributed these effects to the perceived base-rate probability of the predicted events. These context effects are shown to be attributable to the perceived severity of the predicted event as well as to the perceived base rate. Furthermore, there is evidence for strong context effects that are not explained by either of these 2 variables. The implications of these results for the use of verbal probability statements in the communication of probability information are discussed.
Journal of Experimental Psychology-learning Memory and Cognition, 1999
Past research has demonstrated that interpretations of vague verbal forecasts (e.g., "likely") differ as a function of the context to which they refer. Experiments 1 and 2 demonstrate that precise numeric forecasts (e.g., "70%") are also susceptible to such context effects. Participants read descriptions of target events and experts' numeric forecasts. Perceptions of certainty, expressed on nonnumeric scales, differed as a function of context manipulations. The results of Experiments 3a, 3b, and 4 indicate that these effects can be mediated by perceptions of an event's representativeness independently of subjective base rates. The results are also consistent with the idea that two types of semi-independent processingassociative and rule based-can have important influences on perceptions of certainty. Implications of this distinction for research on judgments and decisions under uncertainty are discussed.