Data Classification

 


    For this week's cartography lab, I created a map of the distribution of Miami Dade county's senior citizen population. I used four different data classifications; quantile, standard deviation, natural breaks, and equal interval. The use of the four different classifications was to show how the data can be displayed in different ways, and how this can alter how an audience views a map. According to the attribute table, Census Tract 58.02 was the area with the highest percentage of senior citizens, and this is displayed the best in the equal interval map. The equal interval map distributed the data into equal ranges, which concentrated color into a few areas that have a large senior citizen population. If someone wanted to learn more about the demographic of the county in relation to senior citizens, the equal interval map would be easiest to interpret. I enjoyed this lab because it was interesting to see how the different data classifications can make a map look so different. 

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