Module 3: Data Classification Lab Assignment

I tried to decide which method of classification best represented the given data by evaluating which of the four methods offered the clearest picture of the data. It was easy for me to rule out the standard deviation classification because this classification would not allow me to use a color ramp similar to the others. Additionally, with only four breaks in the data, I felt that far too many tracts fell within the smallest break. I felt the same way about the equal interval classification.

I decided that the quantile data classification portrayed the best model of the data. On the map below, I made some key changes to a quantile style map to further enhance the portrayal of the data. First, I created eight breaks. One problem with five breaks was the large range of data included in the 5th class. There is still a significant range in my 8th class; however, I believe that this is appropriate as I am placing an obvious emphasis on demographics. After that, I wanted to change to a color ramp that did not directly correlate with racial demographics. Such a color pattern could be interpreted as insensitive and offensive, and I wanted to avoid this. My final product resulted in a map with enough color variance and enough classes to easily interpret the data provided.