Module 4 : Data Classification

 For this module, we learned about multiple different classification methods but for the lab, we focused on four: Natural Breaks, Quantile, Equal Interval, and Standard Deviation. We were tasked with using each method individually to portray the population amounts of 65 and up individuals otherwise known as senior citizens. The two images below showcase the four methods being implemented on each map using the data for 65 and up citizens. One is normalized and the other is not. Map A is the one that was not normalized and Map B is the one that was. Map A was easy to put together since the majority of the work was down within the symbology pane. By changing the methods, there was a distinct difference in how the maps looked compared to each other along with the percentage values being calculated. Now with Map B, the normalization feature calculated just the population number by the square foot and thus gave similar looking maps with varying ranges in the legends. Overall the maps were always different based on the calculations. The two maps most similar for both images would be the quantile and natural breaks methods. They produce almost identical maps but the natural breaks were generally more spread out and even than the quantile method map. I think I have a preference for the quantile method because I felt that the calculations were more accurate and it portrayed the information easily and clearly. 

Map A. 

Map B.