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Andrea Saffran
Ludwig Maximilian University of Munich
4Publications
2H-index
5Citations
Publications 4
Newest
#1Christopher Osterhaus (LMU: Ludwig Maximilian University of Munich)H-Index: 1
#2Jaclyn Magee (UW: University of Wisconsin-Madison)H-Index: 1
Last.Martha W. Alibali (UW: University of Wisconsin-Madison)H-Index: 40
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People often have difficulty interpreting covariation data presented in contingency tables. The present study investigates adults’ success and strategy use in interpreting covariation data as a function of two factors that may influence performance: symmetry and context. We hypothesised that symmetrical problems, which involve comparing two candidate causes, would elicit more adequate interpretations than asymmetrical problems, which involve comparing the presence and absence of one candidate ca...
2 CitationsSource
#1Andrea Saffran (LMU: Ludwig Maximilian University of Munich)H-Index: 2
#2Petra Barchfeld (LMU: Ludwig Maximilian University of Munich)H-Index: 5
Last.Beate Sodian (LMU: Ludwig Maximilian University of Munich)H-Index: 31
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Abstract This research investigates children's understanding of the significance of comparisons between data categories for judgments of covariation. Past studies showed that children sometimes neglect some of the relevant data categories. This may occur because children fail to understand the relevance of the comparisons between data categories. To investigate this interpretation, 51 second graders and 43 fourth graders were tested in a between-subject design. In the standard condition, childre...
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#1Andrea SaffranH-Index: 2
#2Petra BarchfeldH-Index: 5
view all 3 authors...
#1Andrea Saffran (LMU: Ludwig Maximilian University of Munich)H-Index: 2
#2Petra Barchfeld (LMU: Ludwig Maximilian University of Munich)H-Index: 5
Last.Martha W. Alibali (UW: University of Wisconsin-Madison)H-Index: 40
view all 4 authors...
In a series of 3 experiments, the authors investigated the influence of symmetry of variables on children’s and adults’ data interpretation. They hypothesized that symmetrical (i.e., present/present) variables would support correct interpretations more than asymmetrical (i.e., present/absent) variables. Participants were asked to judge covariation in a series of data sets presented in contingency tables and to justify their judgments. Participants in Experiments 1 and 2 were elementary school ch...
3 CitationsSource
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