Neat Scaling of Intervals

The term neat scaling is used throughout STATISTICA to refer to the manner in which ranges of values are divided into intervals, so that the resulting interval boundaries and steps between those boundaries are intuitive and readily interpretable (or "understood").

For example, suppose you want to create a histogram for data values in the range from 1 to 10. It would be inefficient to use interval boundaries for the histogram at values such as 1.3, 3.9,  6.5, etc., i.e., to use as a minimum boundary value 1.3, and then a step size of 2.6. A much more intuitive way to divide the range of data values would be to use boundaries like 1, 2, 3, 4, and so on, i.e., a minimum boundary at 1, with step size of 1; or one could use 2, 4, 6, etc, i.e., a minimum boundary of 2 and step size 2.

In general, neat in this context means that category boundaries will be round values ending either in 0, 2, or 5 (e.g., boundaries may be 0.1, 0.2, 0.3, etc.; or 50, 100, 150, etc.). To achieve this, any user-requested lower limit, upper limit, and number of categories will only be approximated.