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Description
Class Summary  

AverageNearestNeighbor  Calculates a nearest neighbor index based on the average distance from each feature to its nearest neighboring feature. 
CalculateAreas  Calculates Area values for each feature in a polygon feature class. 
CalculateDistanceBand  This tool calculates the distance for all features in the input feature class to their nth neighbor (specified in the Neighbors parameter). 
CentralFeature  Identifies the most centrally located feature in a point, line, or polygon feature class. 
ClustersOutliers  Given a set of weighted features, identifies where high or low values cluster spatially, and features with values that are very different from surrounding feature values. 
ClustersOutliersRendered  Given a set of weighted data points, identifies those clusters of points with values similar in magnitude and those clusters of points with very heterogeneous values, then applies a coldtohot type of rendering. 
CollectEvents  Converts event data, such as crimes or disease incidents, to weighted point data The Collect Events tool is contained in the Spatial Statistics Tools tool box. 
CollectEventsRendered  Converts event data to weighted point data and applies a graduated circle rendering to the count field. 
ConvertSpatialWeightsMatrixtoTable  Converts a binary spatial weights matrix file to a table. 
CountRenderer  Applies graduated circle rendering to a count type field of a point feature class. 
DirectionalDistribution  Measures whether a distribution of features exhibits a directional trend (whether features are farther from a specified point in one direction than in another direction). 
DirectionalMean  Identifies the general (mean) direction for a set of lines. 
ExportXYv  Exports feature class coordinates and attribute values to a space, comma, or semicolondelimited ASCII text file. 
GenerateNetworkSpatialWeights  Constructs a spatial weights matrix file (.swm) from a Network dataset which defines spatial relationships among all features in terms of an underlying network structure. 
GenerateSpatialWeightsMatrix  Constructs a spatial weights matrix (.swm) file to represent the spatial relationships among features in a dataset. 
GeographicallyWeightedRegression  Performs GWR, a local form of linear regression used to model spatially varying relationships. 
HighLowClustering  Measures the degree of clustering for either high values or low values The High/Low Clustering (GetisOrd General G) tool is contained in the Spatial Statistics Tools tool box. 
HotSpots  Calculates the GetisOrd Gi* statistic for hot spot analysis. 
HotSpotsRendered  Calculates Gi* statistics and applies a coldtohot type of rendering to the output z scores. 
MeanCenter  Identifies the geographic center (or the center of concentration) for a set of features. 
MultiDistanceSpatialClustering  The MultiDistance Spatial Cluster Analysis (Ripley's Kfunction) tool determines whether a feature class is clustered at multiple different distances. 
OrdinaryLeastSquares  Performs global Ordinary Least Squares linear regression to generate predictions or to model a dependent variable in terms of a its relationships to a set of explanatory variables. 
SpatialAutocorrelation  Measures spatial autocorrelation based on feature locations and attribute values. 
StandardDistance  Measures the degree to which features are concentrated or dispersed around the geometric mean center. 
ZRenderer  Applies a coldtohot graduated color rendering to a field of z scores. 
The Spatial Statistics toolbox contains statistical tools for analyzing the distribution of geographic features: finding the geographic center, identifying statistically significant spatial clusters (hot spots) or outliers, assessing overall patterns of clustering or dispersion, and so on. Spatial statistics differ from traditional statistics in that space and spatial relationships are an integral and implicit component of their mathematics. The tools in the Spatial Statistics toolbox demonstrate a variety of statistical operations appropriate for analyzing geographic data. In addition, for those tools written with python the source code is available to encourage you to learn from, modify, extend and share these and other analysis tools. For more information about these tools and statistical analysis of geographic data in general, see The ESRI Guide to GIS Analysis, Volumes 1 and 2 (Volume 2 discusses the methods in the Spatial Statistics toolbox).
The following toolsets are provided with the Spatial Statistics toolbox at ArcGIS 9.
Name  Description 

Analyzing Patterns Toolset  These tools evaluate if features or attribute values form a clustered, uniform, or random pattern across the region. 
Mapping Clusters Toolset  These tools may be used to identify statistically significant hot spots, cold spots, or spatial outliers. 
Measuring Geographic Distributions Toolset  These tools address questions such as: Where's the center? What's the shape and orientation? How dispersed are the features? 
Utilities Toolset  These tools may be used to reformat data or to render analysis results. 


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