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Abstract Details
Activity Number:
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552
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Type:
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Invited
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Date/Time:
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Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Education
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Abstract - #300223 |
Title:
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Ignoring the Spatial Context in Intro Stats Classes -- And Some Simple Graphical Remedies
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Author(s):
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Juergen Symanzik*+ and Nathan D. Voge
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Companies:
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Utah State University and Utah State University
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Address:
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Department of Mathematics & Statistics, Logan, UT, 84322-3900, USA
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Keywords:
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Introductory Statistics ;
Teaching ;
Maps ;
Graphics ;
Spatial Dependence ;
Spatial Association
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Abstract:
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Statistical data often have a spatial (geographic) context, be it countries of the world, states in the US, counties within a state, cities across the globe, or locations where measurements have been taken. However, most introductory statistics books do not even suggest that such data often are not independent from location, but rather are effected by some spatial association. Remedies are simple: Display data via various map views and briefly discuss which additional information can be extracted from such a graphical representation. In this article, we will visit a variety of popular introductory statistics textbooks and show how some of the data used in examples and exercises can be initially displayed via various map views, such as choropleth maps or micromaps. Students familiar with R should be able to create similar map displays by themselves via several R packages.
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