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Visualizing statistical edutainment: What you see is what you get.

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Title: Visualizing statistical edutainment: What you see is what you get.
Authors: Lesser, Lawrence M.1 (AUTHOR), Pearl, Dennis K.2 (AUTHOR) dkp13@psu.edu
Source: Teaching Statistics. Jul2023, Vol. 45 Issue 3, p131-142. 12p.
Subject Terms: *Educational entertainment, Data visualization, Data science
Abstract: Concepts of data visualization are explored using statistics educational fun items and illustrated by sharing results from the experiment we conducted on cartoon captions. [ABSTRACT FROM AUTHOR]
Copyright of Teaching Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: <searchLink fieldCode="JN" term="%22Teaching+Statistics%22">Teaching Statistics</searchLink>. Jul2023, Vol. 45 Issue 3, p131-142. 12p.
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  Data: Concepts of data visualization are explored using statistics educational fun items and illustrated by sharing results from the experiment we conducted on cartoon captions. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Teaching Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Data science
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              Text: Jul2023
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              Y: 2023
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