Abstract
When making judgments, people often favor information received from a few individual sources over largesample statistical data. Individual information is usually acquired piece by piece, whereas statistical information combines many observations into a single summary. We examined whether this difference in the frequency of encounters affects how data are weighted. In two experiments, subjects read statistical information indicating an event to be rare and contrasting information from individual cases suggesting the event to be common. We controlled whether the individual cases were summarized into a single summary like statistical information, or presented serially, case by case. Subjects’ estimates of event frequencies were higher when the individual cases were presented in serial, rather than summarized, format. A third study demonstrated that subjects treat each data sample as an instance, and do not weight according to sample size. These results support the conclusion that people weight information according to encounter frequency.
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This project was supported by NSF Grants SES-03-25080 and SBE-06-24098 to the second author, by research funds from Rutgers and NSF Grant REC-9720410 to the third author, and by a Rutgers University excellence fellowship and an NSF graduate fellowship awarded to the first author.
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Obrecht, N.A., Chapman, G.B. & Gelman, R. An encounter frequency account of how experience affects likelihood estimation. Memory & Cognition 37, 632–643 (2009). https://doi.org/10.3758/MC.37.5.632
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DOI: https://doi.org/10.3758/MC.37.5.632