DEFINITIONS: A **squared rectangle** is a rectangle dissected into a finite number, two or more, of squares, called the elements of the dissection. If no two of these squares have the same size the squared rectangle is called **perfect**, otherwise it is **imperfect**. The **order** of a squared rectangle is the number of constituent squares. The case in which the squared rectangle is itself a square is called a **squared square**. The dissection is **simple** if it contains no smaller squared rectangle, otherwise it is **compound**. Simple Perfect Squared Squares are SPSSs. 

If we count the number of elements in all the SPSSs of a given order and sum them by frequency we end up with a distribution that looks like positively skewed normal distribution. For example order 32 is the highest order that has been completely enumerated and the number of prime elements in the SPSSs of that order range from 0 to 18. The frequencies across that range are 814, 2018, 5997, 12068, 17515, 20987, 22289, 20652, 16516, 11689, 7290, 3731, 1678, 650, 209, 43, 12, 2, 1. There are 144161 SPSSs in order 32. 

Is using a normal distribution appropriate and correct? Would an Erdos-Kac description be more appropriate? Original Element data are available [here](http://www.squaring.net/downloads/downloads.html#spss).