The ultimate sampling dilemma in experience-based decision making

Fiedler, Klaus

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URN: urn:nbn:de:bsz:180-madoc-25172
Document Type: Working paper
Year of publication: 2007
The title of a journal, publication series: Rationalitätskonzepte, Entscheidungsverhalten und ökonomische Modellierung
Volume: 07-51
Place of publication: Mannheim
Publication language: English
Institution: School of Law and Economics > Sonstige - Fakultät für Rechtswissenschaft und Volkswirtschaftslehre
MADOC publication series: Sonderforschungsbereich 504 > Rationalitätskonzepte, Entscheidungsverhalten und ökonomische Modellierung (Laufzeit 1997 - 2008)
Subject: 150 Psychology
Subject headings (SWD): Entscheidung bei Unsicherheit , Lernen , Informationsverhalten , Auswahlverfahren , Statistik , Bias
Abstract: Computer simulations and two experiments are reported to delineate the ultimate sampling dilemma, which constitutes a serious obstacle to inductive inferences in a probabilistic world. Participants were asked to take the role of a manager who is to make purchasing decisions based on positive versus negative feedback about three providers in two different product domains. When information sampling (from a computerized data base) was over, they had to make inferences about actual differences in the data base from which the sample was drawn (e.g., about the actual superiority of different providers, or about the most likely origins of negatively valenced products). The ultimate sampling dilemma consists in a forced choice between two search strategies that both have their advantages and their drawbacks: natural sampling and deliberate sampling of information relevant to the inference task. Both strategies leave the sample unbiased for specific inferences but create errors or biases for other inferences.
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