The sum of squares, or variation, of a data set is the summed total of the squares of each individual values distance from the mean, the mathematical average of a set. Like variance, the sum of squares is a measure of how densely packed a dataset is. A small sum of squares points to a data set that is mostly similar to the mean, while a large one indicates a data set that is spread out. Along with other measures like standard deviation and variance, the sum of squares helps to give viewers an understanding of how the data is distributed relative to the mean.