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Abstract Details
Activity Number:
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73
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2012 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistical Education
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Abstract - #305569 |
Title:
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A Cognitive Interpretation of Data Analysis
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Author(s):
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Garrett Grolemund*+ and Hadley Wickham
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Companies:
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Rice University and Rice University
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Address:
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Department of Statistics, Houston, TX, 77005, United States
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Keywords:
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Data Analysis ;
Cognitive Science ;
Sensemaking
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Abstract:
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This study treats data analysis as a mental process and examines how this view can be used to improve data analysis methods. Previous study of data analysis has been limited largely to description and introspection. The lack of theory makes data analysis difficult to teach and discuss and may also stymie improvements in data analysis methods. In contrast to existing approaches, we argue that data analysis is a sensemaking task adapted to the use of quantitative data. Under this paradigm, data analysts must balance competing tensions of cognitive limitations and the need for scientific rigor. This creates a set of sequential problems that characterize all data analysis tasks. We present a model of data analysis based on these insights and examine two cognitive phenomena that can adversely affect data analyses: the persistence of false schemas and abductive schema selection. The insights of this model are especially helpful for consultants, applied statisticians, and teachers of data analysis.
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