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Abstract Details
Activity Number:
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522
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Education
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Abstract - #302579 |
Title:
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Spatial Statistics and Cartography Using SOCR
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Author(s):
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Dave A. Zes*+ and Ivo D. Dinov and Nicolas Christou
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Companies:
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University of California at Los Angeles and University of California at Los Angeles and University of California at Los Angeles
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Address:
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Department of Statistics, Los Angeles, CA, 90095,
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Keywords:
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spatial statistics ;
environmental data ;
raster maps ;
vector maps ;
interpolation ;
geostatistics
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Abstract:
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In this paper we present the new spatial statistics and cartography applet of the Statistics Online Computational Resource (SOCR). One of the most appealing aspects of spatial data is their visualization. Using this SOCR applet we have made it easy to import raster and vector maps and overlay data as layers at specific geographic locations defined by their coordinates. Interpolation using the inverse distance method is also available as well as the construction of a raster map using the interpolated values. The analysis of spatial data can be greatly enhanced using maps and geographic information systems tools (GIS). GIS have become popular in recent years and they are encountered in many disciplines. However we have not seen much of their use in statistics, and in particular at introductory level statistics courses. We believe that incorporating spatial data in undergraduate curriculum can engage students and stimulate their interest. Several environmental spatial data sets can be accessed through SOCR.
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