This lab exercise challenged us with the task of analyzing the senior citizen population of Miam-Dade County, FL using four different classification methods (Natural Breaks, Quantile, Equal Interval, and Standard Deviation). We first analyzed the data based on the population percentage of senior citizens per census tract, and then again as a measure of population density per square mile per census tract. Our objective was to determine the best classification method and type of data (percentage or density) to identify the population distribution within the county.
The best way to analyze the data in terms of actual numbers on the ground is using population density per square mile. This method gives you an accurate idea of where senior citizens are concentrated so that you may allocate your resources in the most cost effective and efficient manner possible. Analyzing by percentage population gives a false sense of where the largest number of senior citizens actually resides. As such I have included the maps that break down the population by density per square mile.
The best classification schemes for understanding the actual distribution of senior citizens are Natural Breaks and Quantile. Depending on the county's resources and management objectives, you may use either Quantile or Natural Breaks to effectively achieve the county's goals. They both give a decent idea of where the greatest concentration of senior citizens reside and if the goals were spelled out clearly, the data breaks could be set manually for a potentially more focused map of density per census tract. For this exercise, I found the most useful to be Quantile and Natural Breaks, but all four are useful in gaining a more thorough understanding of the population distribution of senior citizens.
Below is the percentage distribution for reference purposes:
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