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:**ΣX

^{2}– ((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**

Explanation

ΣX^{2} = 15157

(ΣX)^{2} = 182329

n = 14

Sum of squares = 15157 – (182329 / 14) = 2133.50