The mean squares (MS), which are the adjusted mean squares, measure how much variation a term or a model explains, assuming that all other terms are in the model, regardless of the order they were entered. Unlike adjusted sums of squares, adjusted mean squares consider the degrees of freedom.
The adjusted mean square error (also called MSE or s2) is the variance around the fitted values.
Minitab uses the adjusted mean square to calculate the p-value for a term. Minitab also uses the adjusted mean squares to calculate the adjusted R2 statistic. Usually, you interpret the p-values and the adjusted R2 statistic instead of the adjusted mean squares.