This week in Cartographic Skills, we went through an ESRI training course on using spatial statistics to explore data in GIS before performing any analysis. ArcMap includes various tools that allow you to look at things like how your data is distributed, whether it's autocorrelated (meaning whether values are dependent on location -- pretty important for spatial analysis!), how variable it is across your study area, and whether there are any identifiable trends. All of this information can then be used to make an informed decision about what kind of analysis would be best to use. These tools also offer several ways to spot outliers in the data so that they can be corrected or removed so as not to skew the analysis.
While exploring the statistical tools available in ArcMap, we worked with temperature data collected from weather monitoring stations in western Europe. The map below shows the geographic distribution of those stations, as well as the mean center and median center calculated from the locations of all the monitoring stations in the dataset. The red oval indicates the directional distribution (roughly east-west) of the location data, and encircles all the stations whose location is within one standard deviation of the mean center. All of these were calculated within ArcMap using tools found in the standard spatial statistics toolbox.
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