Spatial Autocorrelation

Spatial Autocorrelation

Methodology

To analyze how demographic variables cluster geographically, we use Spatial Autocorrelation. This methodology tells us whether regions with similar demographic features are geographically close to each other.

Moran's I

We calculated Global Moran's I to test for overall spatial clustering in variables like Population Density and Median Age. A positive Moran's I indicates that regions with similar values tend to cluster together (e.g., older regions bordering other older regions).

LISA (Local Indicators of Spatial Association)

We utilized Local Moran's I to identify specific local clusters and spatial outliers:

• High-High Clusters: Regions with high values surrounded by high values.
• Low-Low Clusters: Regions with low values surrounded by low values.
• Spatial Outliers (High-Low / Low-High): Regions that differ significantly from their neighbors. Results from these models can be found in the Spatial Autocorrelation directory.