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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp013j3332402
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dc.contributorBotvinick, Matthew-
dc.contributor.advisorNiv, Yael-
dc.contributor.authorDombrowski, Katya-
dc.date.accessioned2014-07-03T20:03:45Z-
dc.date.available2014-07-03T20:03:45Z-
dc.date.created2014-04-
dc.date.issued2014-07-03-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp013j3332402-
dc.description.abstractWhen making decisions in complex environments, how can people separate what is important from what can be ignored? This study used the common task of choosing an item from a list to uncover whether there are specific strategies for solving this problem across both people and domains. Two types of everyday decisions, choosing food from a menu and choosing undergraduate courses from a list, were tested using online, as well as in-lab, experiments. The results revealed that participants tended to first narrow down their options based on broad information and then come to a final decision after looking at the short list of options in more detail. The results from this experiment also suggested that participants made these decisions based on only a few criteria at a time, where some criteria were significantly more important across participants. Therefore, despite the complexity and uniqueness of a given scenario, there may be common strategies used across people and domains in everyday decision-making. These processes may allow for less cognitive demand when making decisions, which could lead to a more efficient process overall. Further experiments could reveal whether or not these behavioral results correlate with similar neural networks, across both people and domains, as well.en_US
dc.format.extent99 pages*
dc.language.isoen_USen_US
dc.titleThe Statistics of Natural Tasks: How People Make Everyday Decisions in a Complex Worlden_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2014en_US
pu.departmentPsychologyen_US
pu.pdf.coverpageSeniorThesisCoverPage-
Appears in Collections:Psychology, 1930-2020

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