Week 3: Data Classification

The first map is a comparison of four data classification methods (Equal Interval, Standard Deviation, Quantile, and Natural Break). The objective is to discern the optimum data classification method for the map reader to best understand the relationship being described (i.e. black population) and to clarify distinctions in the census data among census blocks in Escambia County. NOTE: One of the revelations that came to me from this exercise is that the cartographer may inadvertantly or intentionally direct the observer toward an interpretation of the data based on the choice of data classification. Because the typical observer will look first at the general appearance of attributes on the figure (and then, subsequently, at the details...i.e. legend details, data classification-type, etc.)...it is critically important that a cartographer practice with the highest level of integrity and character so as not to falsely direct the interpretation of data through one's map.



I have chosen the Quantile Classification to be the optimum choice for map selection that presents these data. Based on resolution of the legends (all legends held constant at "4" categories), the Quantile Data Classification gives the broadest spread of categories throughout the map while the other data classification methods each produce a monotone spread throughout Escambia County with the exception of the urban area (Pensacola). As long as an informative legend is provide that categorizes the population ranges, the Quantile method permits the broadest zone distinctions and enhances the interpretive value of the map.