Mean square in ANOVA
= Mean square in ANOVA
{title2=$MS=SS/d$}
= Mean squares in ANOVA
{synonym}
A <mean square in ANOVA> divides a <sum of squares in ANOVA> by its positive number $d$ of <statistical degrees of freedom>. If the corresponding residual subspace has scalar error <covariance> $\lambda I$, its <expectation> is $\lambda$. Its scale depends on whether raw observations or group means were projected.