Cartographic Skills Module 6: Data Classification

Data classification was the focus of this week's Cartographic Skills Lab.  The creation of a map comparing four different methods of data classification (Equal Interval, Quantile, Standard Deviation, and Natural Breaks) was completed by creating four data frames within one map and then applying a method of data classification to each of the data frames.  As careful as I thought I was being, I learned the hard way that an oversight can produce an erroneous map. Printing out a review copy of the map prior to submitting it helped me to catch a couple of major errors.  Nice-looking maps aren't especially helpful if the information is wrong.

Comparison of Four Methods of Data Classification as Applied to
Black/African-American Percentage of Population
Escambia County, Florida, 2000

After correcting the errors in the data classification method comparison map (involving legends for certain classification methods being applied to the wrong data frames), it was easy enough to save the map as a new document and then make some adjustments to complete a map of the data classification method which I thought best for this particular purpose.  In this situation I felt the Natural Breaks method was best suited.  The Natural Breaks method takes into consideration clusters of information which can be overlooked by using the Equal Interval method.  The Standard Deviation method doesn't seem to be very user friendly for this purpose.  The Natural Breaks method puts more emphasis on groups of similar data and is easy to interpret which seemed appropriate for the audience likely to use a map like this.

Natural Breaks Method of Data Classification Applied to
Black/African-American Percentage of Population
Escambia County, Florida, 2000