JSM 2011 Online Program

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Abstract Details

Activity Number: 552
Type: Invited
Date/Time: Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Education
Abstract - #300223
Title: Ignoring the Spatial Context in Intro Stats Classes -- And Some Simple Graphical Remedies
Author(s): Juergen Symanzik*+ and Nathan D. Voge
Companies: Utah State University and Utah State University
Address: Department of Mathematics & Statistics, Logan, UT, 84322-3900, USA
Keywords: Introductory Statistics ; Teaching ; Maps ; Graphics ; Spatial Dependence ; Spatial Association
Abstract:

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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