1. Spatial autocorrelation can also occur geographic areas are likely to have similar errors.2. Negative values indicate negative spatial autocorrelation and positive values indicate positive spatial autocorrelation. 3. Negative values indicate negative spatial autocorrelation and positive values indicate positive spatial autocorrelation . 4. Like spatial autocorrelation , this can be a useful tool for spatial prediction. 5. Classic spatial autocorrelation statistics include Getis's G and the standard deviational ellipse. 6. The latter is a well-known statistic that accounts for the Global spatial autocorrelation . 7. Spatial autocorrelation statistics measure and analyze the degree of dependency among observations in a geographic space.8. Classic spatial autocorrelation statistics compare the spatial weights to the covariance relationship at pairs of locations. 9. There may be spatial trends and spatial autocorrelation in the variables that violate statistical assumptions of regression. 10. Spatial autocorrelation is more complex than autocorrelation because the correlation is multi-dimensional and bi-directional.
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