Module 4: Classification Methods

 Understanding Data Classification 

In this week's lab, there are four common data classification methods that are used to present data; Equal Interval, Quantile, Standard Deviation, and Natural Break (Jenks ). 

Our lab allowed us to explore the different types of data classification and visualize how each classification is different from the other. We used data from Florida Geographic Database Library 2010 Census Data of people in Dale County, FL to find the percentage of individuals over 65. There are two maps, one on Classification Methods for Senior Population over 65 and another Classification Methods for Senior Population over 65 per Sq. Mile. 







Observations:

Natural Break (Jenks ) Classification - Considers natural groups within the data. It minimizes extreme values between data values in the same class and maximizes differences between classes. Using the Natural Break Classification would use the natural grouping of the data to replicate how populations of people are random and often groups themselves based on physical features such as locations of senior care, medical facilities, and senior communities. 

Equal Interval Classification- Takes all values from lowest to highest and creates equal distanced categories. Then the data records are categorized by within each class. Although this method is easy to understand, the class limits don’t consider data distributed on a number line. Based on the map’s presentation, the equal interval classifications seem to only show three of the 5 classes based on how the data is grouped. Data values between the highest and lowest values were either categorized for the lower or higher values not accurately depicting the data of the map.

Quantile Classification- Equally divides the total number of values into desired number of classes. Similar to the equal interval, quantile classifications don’t have empty or class with missing values, but some data such as the darkest green values where there should be one area with the highest value is shown in Standard deviation, equal interval, and natural breaks classification maps, quantile has many more values that could have similar values in different classes or very different values in the same class.

Standard Deviation Classification - Classes are created by grouping the standard deviation from the average values that provide visual variability. This considers data that is distributed on a number line. Based on the presentation of the standard deviation classification map, there are more classes that can show more accuracy in the data, but reviewing the legend not many map readers are informed what the standard deviation values mean and how it relates to the map’s presented data.



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