Module 4 Data Classification

In this weeks lab we took the 2010 Miami Dade County, Florida Census and applied it to the population living there of 65 and older. In doing do we created two different maps with the first showing the percentage in each area and the other documenting it in square miles. In both of these maps there was applied in 4 smaller maps the different methods for evaluating areas in projects such as these. Natural Breaks, Quantile, Standard Deviation and Equal Interval. Each one of these classifications puts a small variation in how each of the data's read with all of the maps being colored in for whatever bracket of numbers to which they fell into. The equal interval option breaks the map into 5 equal measurements of the final number giving a square split. The quantile method takes the highest and lowest numbers to determine to attempt to find the midway point. The standard deviation method breaks the data into a graph with the most data centered around the average and the rest of the data shrinking moving outward. With the natural breaks method attempts to minimize the in-class variance while also maximizing the inter-class variance. Each of these methods allows the data to be rewritten and re-read in multiple ways so all of the data can be interpreted in the most varied ways possible for clarification. This week I learned not only how to optimize more methods in ArcGis but I also was able to process data in a way to which I had never been exposed to before. All of these things have build on each other to help me properly understand how to process and therefore put forth census data in the future.