Crime Analysis

Crime, to some degree, is a function of human society.  When humans live in groups we tend to declare certain actions as being "wrong," and structure punishments and consequences correspondingly.  What specific actions are considered criminal obviously varies across space and time, and the motivations underlying those actions do as well, but analysis of where criminal activity occurs is an interesting application of statistical principles in spatial analysis.  The where doesn't necessarily give us the why, but it does make for some compelling theories, and a good introduction to spatial statistics in GIS.  

  
There are several decent measures of statistical "hotspots" one can employ, and the three used above to look at burglaries in Albuquerque, NM are Local Moran's I, Kernel Density and Grid Overlay.  All of the measures attempt to categorize, to some degree, the areas in which crimes are most frequent, by way of examination of their mapped locations.  The tools available in GIS to complete this analysis range from (relatively) simple point-in-polygon counts involved with Grid Overlay to the Z-scores and p-values used in the Local Moran's I.  Although all three methods used the same source data, clearly they have arrived at different resulting crime "hotspot" areas.  The variations as such are a function of the varied techniques involved in calculating statistically significant areas of highest crime.