The sum of squared deviations, more commonly called the sum of squares, is a way to measure the variability of the values in a dataset. The sum of squares is calculated as:
Sum of squares: ΣX2 – ((ΣX)2 / N)
To find the sum of squares for a given dataset, simply enter the comma-separated values in the box below and then click the “Calculate” button.
Sum of squares = 2133.50
ΣX2 = 15157
(ΣX)2 = 182329
n = 14
Sum of squares = 15157 – (182329 / 14) = 2133.50