Using Spatial Autocorrelation to analyze patterns

The Spatial Autocorrelation tool measures spatial autocorrelation by simultaneously measuring feature locations and attribute values. If features that are close together have similar values, then that is said to be clustering. However, if features that are close together have dissimilar values, then they are said to be dispersed. This tool outputs a Moran's I index value along with a z-score, and a p-value.

In this exercise, you'll use the Spatial Autocorrelation tool to analyze home sales by census tract.

Preparation

Let's get prepared by performing the following steps for using the Spatial Autocorrelation tool to analyze patterns:

1. Open ArcMap with the C:GeospatialTrainingSpatialStatsSeattleNeighborhoodBurglary.mxd file. You should see a polygon feature class called Seattle Neighborhood Burglary, as shown in the following screenshot:

2. We'll first symbolize the data, so we have an idea about the contents of the data we'll be examining in this exercise...