ERIC Number: EJ1141161
Record Type: Journal
Publication Date: 2017-May
Pages: 13
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0364-0213
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Available Date: N/A
When Absence of Evidence Is Evidence of Absence: Rational Inferences from Absent Data
Hsu, Anne S.; Horng, Andy; Griffiths, Thomas L.; Chater, Nick
Cognitive Science, v41 suppl 5 p1155-1167 May 2017
Identifying patterns in the world requires noticing not only unusual occurrences, but also unusual absences. We examined how people learn from absences, manipulating the extent to which an absence is expected. People can make two types of inferences from the absence of an event: either the event is possible but has not yet occurred, or the event never occurs. A rational analysis using Bayesian inference predicts that inferences from absent data should depend on how much the absence is expected to occur, with less probable absences being more salient. We tested this prediction in two experiments in which we elicited people's judgments about patterns in the data as a function of absence salience. We found that people were able to decide that absences either were mere coincidences or were indicative of a significant pattern in the data in a manner that was consistent with predictions of a simple Bayesian model.
Descriptors: Statistical Inference, Bayesian Statistics, Evidence, Prediction, Probability, Experiments, Decision Making
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
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