Module 4: Data Classification

This module introduced different methods of data classification. We used common methods of classification for choropleth mapping (equal interval, quantile, standard deviation, and natural breaks). I used 2010 census data from FGDL to map the senior citizen population distribution in Miami Dade County, Florida.

My map displays the percentage of the population 65+ by four different methods of data classification covered in this lab. Percentage of the population better shows where seniors are distributed across the county. Other data I used in this lab was population count normalized by area. That method could misrepresent the data. The same number of seniors in a large tract could look different than the same number in a smaller area tract.

The equal interval method equally divides the total data range into five classes. This makes classes with equal ranges. For this data set, equal interval groups all counties with a 65+ population of 15.83% or less into one class. The majority of census tracts fall into this class. Equal interval conceals the variation in lower values.

Second, the quantile method creates classes with an equal number of observations. The quantile method presents the variation in the data set’s lower values better than the equal interval. However, the highest class contains values from 19.94%-79.17%. This is the opposite issue of equal interval, concealing patterns in the higher range. 

Third, the standard deviation classification method divides equal classes based on the standard deviation. The data is presented pretty well here. It shows the variation in the range of values well. A user needs knowledge of statistics for this data presentation to make sense.

Fourth, the natural break method uses algorithms are used in this method to create classes. This minimizes differences within classes and increases the difference between them. I think this method shows the pattern pretty well. There is a large range of values (29.85%-79.17%) in the highest class.

The best method to display the data for an audience looking to target the senior citizen population would be the equal interval classification method. This is because three of the five classes are displaying tracts with more than 31.67% senior population. This gives the audience a more detailed breakdown of the higher percentages than other classification methods. They can then specifically target tracts with a senior citizen population they want.