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dc.contributor.authorBruckmaier, Georg
dc.contributor.authorBinder, Karin
dc.contributor.authorKrauss, Stefan
dc.contributor.authorKufner, Han-Min
dc.date.accessioned2020-03-10T10:14:45Z
dc.date.available2020-03-10T10:14:45Z
dc.date.issued2019
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/30731
dc.identifier.urihttp://dx.doi.org/10.26041/fhnw-2013
dc.description.abstractChanging the information format from probabilities into frequencies as well as employing appropriate visualizations such as tree diagrams or 2 × 2 tables are important tools that can facilitate people’s statistical reasoning. Previous studies have shown that despite their widespread use in statistical textbooks, both of those visualization types are only of restricted help when they are provided with probabilities, but that they can foster insight when presented with frequencies instead. In the present study, we attempt to replicate this effect and also examine, by the method of eye tracking, why probabilistic 2 × 2 tables and tree diagrams do not facilitate reasoning with regard to Bayesian inferences (i.e., determining what errors occur and whether they can be explained by scan paths), and why the same visualizations are of great help to an individual when they are combined with frequencies. All ten inferences of N = 24 participants were based solely on tree diagrams or 2 × 2 tables that presented either the famous “mammography context” or an “economics context” (without additional textual wording). We first asked participants for marginal, conjoint, and (non-inverted) conditional probabilities (or frequencies), followed by related Bayesian tasks. While solution rates were higher for natural frequency questions as compared to probability versions, eye-tracking analyses indeed yielded noticeable differences regarding eye movements between correct and incorrect solutions. For instance, heat maps (aggregated scan paths) of distinct results differed remarkably, thereby making correct and faulty strategies visible in the line of theoretical classifications. Moreover, the inherent structure of 2 × 2 tables seems to help participants avoid certain Bayesian mistakes (e.g., “Fisherian” error) while tree diagrams seem to help steer them away from others (e.g., “joint occurrence”). We will discuss resulting educational consequences at the end of the paper.en_US
dc.language.isoen_USen_US
dc.relation.ispartofFrontiers in Psychologyen_US
dc.accessRightsAnonymous*
dc.subjectBayesian reasoningen_US
dc.subjecteye trackingen_US
dc.subject2 x 2 tableen_US
dc.subjecttree diagramen_US
dc.subjectnatural frequenciesen_US
dc.subjectprobabilitiesen_US
dc.subject.ddc150 - Psychologieen_US
dc.titleAn eye-tracking study of statistical reasoning with tree diagrams and 2 x 2 tablesen_US
dc.type01 - Zeitschriftenartikel, Journalartikel oder Magazin*
dc.volume10en_US
dc.issue632en_US
dc.audienceScienceen_US
fhnw.publicationStatePublisheden_US
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publicationen_US
fhnw.InventedHereYesen_US
fhnw.PublishedSwitzerlandYesen_US
fhnw.IsStudentsWorknoen_US
fhnw.publicationOnlineJaen_US


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