When dealing with quantitative data, which method divides the data into segments of equal size?

When managing quantitative data in GIS, the method that divides the data into segments of equal size is known as the equal interval method. This approach defines a set number of classes and ensures that each class has the same range of values. For example, if you have a dataset ranging from 0 to 100 and want to create five equal intervals, each class would cover a range of 20 units (0-20, 20-40, etc.).

The equal interval method is particularly useful because it provides a straightforward way to visualize data, making it easier to understand and interpret distribution patterns within the dataset. This method contrasts with the quantile method, which divides data into groups that each contain the same number of observations, and the natural breaks method, which seeks to minimize variance within groups while maximizing variance between groups. The defined interval method sets specific, predetermined ranges but does not guarantee equal size for all segments unless specifically designed that way. In summary, the equal interval method is ideal for achieving a uniform segmentation of quantitative data.