Equal
interval (sometimes
called
Equal steps) classification.
In this method the class width is equal for all classes. The technique
works by subtracting the highest value from the lowest value,
and the result is divided by the number of classes. Let us assume
we want to create 5 classes out of this data set: ((1000-10)/5)=
198. This result (198) is used as a constant C in the
following formula to determine the class boundaries:
Lowest
value + C + C + C + C + C = highest value
Equal
interval classification is appropriate when the data values are
reasonably evenly spread throughout the data range. Examine the
histogram: if the histogram has a fairly
flat trend, the data values are evenly spread.

Fig
1. Demographic map, six classes. Equal interval classification
; monochromatic greyscale.
Exercise:
Using the interactive classification applet determine a variable
suitable for classification using the Equal interval method and
map it.
You
can open the applet in a new window by clicking
on this link. and refer back and forth with this window when
needed.