mean squared error

Let $n$ be the total number of observations, $i\in {\mathbb{N}}_{[1,n]}$ an index and $y_i$ be the $i-$th observation. The mean squared error is given by $\text{MSE}=\frac{1}{n}{\sum }_{i=1}^n(y_i-{\hat{y}}_i{)}^2.$

The mean squarred error is related to residual sum of squares (RSS) by the equation $\text{MSE}=\frac{\text{RSS}}{n}.$