What statistical tools would be good for visual representation of non-numeric data? For example, I have data different crimes committed throughout the City of Boston. What would be good ways to represent different types of crimes committed in each neighborhood with spatial statistics, spatial analyst or geostatistics tools?

I've done a density analysis, showing crimes per 1,000 residents and crimes per square mile. I've also done a point density raster, and have show the mean center of all crimes. These aren't quite satisfying, though. I'm looking for something more.

A big problem is that a lot of the statistical tools want to use attribute data that is numerical. I could theoretically apply a number to each type of crime, say 1 for burglaries, 2 for arson, etc., but this is all made up. There is no inherent numerical value to any given type of crime.

So I appreciate any thoughts you all have.

Thanks.

Dont be tempted by conversion...a numeric category is the same as a text category data. You have nominal data which has a spatial location leaving you with counts, counts per unit area (ie by neighborhood). Some of the areal statistics test could assess whether there was any clustering (but be aware of the statistical assumptions of those appropriate to interval/ratio data). Joins count statistics (not implemented directly in ArcMap) is appropriate for such a task and some may argue Moran's.

With the point density tool, I presume you don't have the actual location of the crimes so measures of mean center should be considered with caution. You could produce ranks of some of your density data and map it.

I would make sure that you avoid the temptation to apply the "latest" in terms of spatial mapping and ensure that the data you do have and the statistical methods you employ conform to the underlying assumptions of your data and just because something looks significant doesn't mean it is