The Impact of Visualizing Nested Sets. An Empirical Study on Tree Diagrams and Unit Squares

dc.date.accessioned2017-06-26T13:42:55Z
dc.date.available2017-06-26T13:42:55Z
dc.date.issued2017-01-06
dc.description.sponsorshipGefördert durch den Publikationsfonds der Universität Kassel
dc.identifier.issn1664-1078
dc.identifier.uriurn:nbn:de:hebis:34-2017062652837
dc.identifier.urihttp://hdl.handle.net/123456789/2017062652837
dc.language.isoeng
dc.relation.doidoi:10.3389/fpsyg.2016.02026
dc.rightsUrheberrechtlich geschützt
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/
dc.subjectBayesian reasoningeng
dc.subjectvisualizationeng
dc.subjectunit squareeng
dc.subjecttree diagrameng
dc.subjectnested setseng
dc.subject.ddc510
dc.titleThe Impact of Visualizing Nested Sets. An Empirical Study on Tree Diagrams and Unit Squareseng
dc.typeAufsatz
dcterms.abstractIt is an ongoing debate, what properties of visualizations increase people’s performance when solving Bayesian reasoning tasks. In the discussion of the properties of two visualizations, i.e., the tree diagram and the unit square, we emphasize how both visualizations make relevant subset relations transparent. Actually, the unit square with natural frequencies reveals the subset relation that is essential for the Bayes’ rule in a numerical and geometrical way whereas the tree diagram with natural frequencies does it only in a numerical way. Accordingly, in a first experiment with 148 university students, the unit square outperformed the tree diagram when referring to the students’ ability to quantify the subset relation that must be applied in Bayes’ rule. As hypothesized, in a second experiment with 143 students, the unit square was significantly more effective when the students’ performance in tasks based on Bayes’ rule was regarded. Our results could inform the debate referring to Bayesian reasoning since we found that the graphical transparency of nested sets could explain these visualizations’ effect.eng
dcterms.accessRightsopen access
dcterms.bibliographicCitationIn: Frontiers in psychology. - Lausanne : Frontiers Research Foundation, 2017, 7, 2026, 1-11
dcterms.creatorBöcherer-Linder, Katharina
dcterms.creatorEichler, Andreas

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