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What is z-score in spatial autocorrelation?
Using the spatial autocorrelation tool in ArcGIS, the checkerboard pattern generates a Moran’s index of -1.00 with a z-score of -7.59. (Remember that the z-score indicates the statistical significance given the number of features in the dataset).
How is Global Moran’s I calculated?
Calculations for Moran’s I are based on a weighted matrix, with units i and j. Similarities between units is calculated as the product of the differences between yi and yj with the overall mean. The Moran’s statistic is calculated using the basic form, which is divided by the sample variance:s2 = (Σ(yi– ̄y)2)/n).
Should I use Moran’s I or Geary’s C?
Geary’s C is inversely related to Moran’s I, but it is not identical. Moran’s I is a measure of global spatial autocorrelation, while Geary’s C is more sensitive to local spatial autocorrelation. Geary’s C is also known as Geary’s contiguity ratio or simply Geary’s ratio.
How does global Moran’s I measure spatial autocorrelation?
Measures spatial autocorrelation based on feature locations and attribute values using the Global Moran’s I statistic. The Spatial Autocorrelation tool returns five values: the Moran’s I Index, Expected Index, Variance, z-score, and p-value.
Is the spatial autocorrelation tool an inferential statistic?
The Spatial Autocorrelation (Global Moran’s I) tool is an inferential statistic, which means that the results of the analysis are always interpreted within the context of its null hypothesis.
What does the z score of Moran’s I indicate?
When the z-score or p-value indicates statistical significance, a positive Moran’s I index value indicates tendency toward clustering, while a negative Moran’s I index value indicates tendency toward dispersion. This tool calculates a z-score and p-value to indicate whether you can reject the null hypotheses.
What are the values of Moran’s I in ArcGIS?
The Spatial Autocorrelation tool returns five values: the Moran’s I Index, Expected Index, Variance, z-score, and p-value. These values are accessible from the Results window and are also passed as derived output values for potential use in models or scripts.