In statistics, typically mean squares = sum squares / df.
For example, the estimator for variance is sample variance, which is equal to sum squares / (sample size - 1), where (sample size-1) is the df for sum squares. There is a (-1) term because you estimate the sample mean, thereby loosing one df.