1. Classification
Ming-Chun Lee

2. Classification How are Continuous Data Categorized in Symbology?
Classification Methods
Equal Interval/Defined Interval
Place Breaks at Equal Intervals, Specifying Number or Width of Breaks
Standard Deviation
Place Breaks at Equal Standard Deviations From the Mean Value
Quantile
Place Breaks Such That Groups Have Equal Size Memberships
Natural Breaks
Place Breaks Between Clusters of Data
Manual Breaks

3. Equal Interval/Defined Interval
Lecture 12

4. Equal Interval/Defined Interval
Guarantees a linear relationship between the data values and the color selected

5. Standard Deviation
Lecture 12

6. Standard Deviation
Similar to Equal Interval, but uses a statistical basis for determining the interval size

7. Quantile
Lecture 12

8. Quantile
Guarantees that each color will be assigned to approximately the same number of features
Effectively divides your data into equally-sized groups
Results in Greatest Overall Differentiation

9. Natural Breaks
Lecture 12

10. Natural Breaks Uses an algorithm to place breaks such that:
The variance within groups is minimized, and
The variance between groups is maximized
Results will tend to be irregularly-sized intervals
This is the default in ArcMap

11. Manual Breaks
Lecture 12

12. Manual Breaks
Can reflect policy- based or arbitrary thresholds and categories
Tedious to set up

13. Classifications: When to Use
Equal Interval
You want to be able to compare relative values using the colors
Standard Deviation
You expect your data to be normally distributed
Quantile
You want your breaks to be narrower in clusters of data
Natural Breaks
You want to use your data to identify clusters of values
Manual Breaks
You have an external source for setting breaks