is monte carlo simulation used in place of normal approximation? I can't find any mention of monte carlo on the tools' help pages. In fact what i found appears to be conflicting documentations. According to your documentation for Getis-Ord's G for example, '...The Z scores are reliable (even with skewed data) as long as each feature is associated with several neighbors (approximately 8, as a rule of thumb). This tool can be applied to skewed data because it is "asymptotically normal". ' This suggests p-values were computed usig normal approximation. But on your p-value documentation page, you say 'A common alternative null hypothesis, not implemented for the spatial statistics toolbox, is the normalization null hypothesis. The normalization null hypothesis postulates that the observed values are derived from an infinitely large, normally distributed population of values through some random sampling process.' I am really confused as to what method is used to get the p-values for LISA and local G statistics and would apreciate any clarification! thx!