Telling Data Stories: Essential Dialogues for Comparative<br>Reasoning


Authors: 
Maxine Pfannkuch, Matt Regan, Chris Wild, and Nicholas J. Horton
Volume: 
18(1)
Pages: 
online
Year: 
2010
Publisher: 
Journal of Statistics education
URL: 
http://www.amstat.org/publications/jse/v18n1/pfannkuch.pdf
Abstract: 

Language and the telling of data stories have fundamental roles in advancing the GAISE <br><br>agenda of shifting the emphasis in statistics education from the operation of sets of <br><br>procedures towards conceptual understanding and communication. In this paper we discuss <br><br>some of the major issues surrounding story telling in statistics, challenge current practices, <br><br>open debates about what constitutes good verbalization of structure in graphical and<br><br>numerical summaries, and attempt to clarify what underlying concepts should be brought to <br><br>students  attention, and how. Narrowing in on the particular problem of comparing groups, <br><br>we propose that instead of simply reading and interpreting coded information from graphs, <br><br>students should engage in understanding and verbalizing the rich conceptual repertoire <br><br>underpinning comparisons using plots. These essential data-dialogues include paying <br><br>attention to language, invoking descriptive and inferential thoughts, and determining <br><br>informally whether claims can be made about the underlying populations from the sample <br><br>data. A detailed teacher guide on comparative reasoning is presented and discussed.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education

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