Spatial Autocorrelation: Significance Analysis

This lecture covers the significance analysis of spatial autocorrelation using Moran's I and random permutations. It explains the concept of observed and random situations, permutation histograms, pseudo p-values, and the calculation of significance. The instructor demonstrates the process step by step, emphasizing the importance of spatial weighting and the interpretation of Moran's I values. The lecture concludes with a summary of key considerations in setting the neighborhood for spatial analysis.