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Using the Spatial Statistics Toolbox

While much can be learned about spatial relationships through visually inspecting the distribution of features on a map, applications in areas such as crime analysis, epidemiology, wildlife biology, and retail analysis often require a more thorough investigation of the data. Spatial statistics provide more advanced methods for comparing geographic distributions, modeling geographic relationships, and exploring unknown conditions.

The Spatial Statistics toolbox, part of the geoprocessing framework in ArcGIS 9, provides tools that apply statistical operations that are appropriate for analyzing geographic data. Because these tools are used in a GIS environment, users can take advantage of the other tools in GIS for managing large datasets and transforming and visualizing data.

The Python source code for most of the tools in the Spatial Statistics toolbox is provided so users can learn more about their operation as well as easily modify or extend them. Extensive information in the online help describes the statistical methods employed by each tool.

The articles in this section demonstrate the value of using the tools in the Spatial Statistics toolbox to explore and evaluate data in order to arrive at better answers. For more information about these tools and spatial data analysis, see the Esri Guide to GIS Analysis, Spatial Measurements and Statistics, Volume 2 by Andy Mitchell. This Esri Press book is scheduled for release in the third quarter of 2005.

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