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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
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.