In each of the models, the VI breaks up the total sum of squares, tss, a measure of the total variation of the data from the overall population mean, into a number of component sums of squares.
tss = ssa + ssb + ssc + ssab + ssac + ssbc + ssabc + sse
Each component in the sum tss is a measure of variation attributed to a certain factor or interaction among the factors. Here ssa is a measure of the variation due to factor A; ssb is a measure of the variation due to factor B; ssc is a measure of the variation due to factor c; ssab is a measure of the variation due to the interaction between factors A and B; and so on for ssac, ssbc, and ssabc. Also, sse is a measure of the variation due to random fluctuation. The VI divides each by its own degrees of freedom to obtain the corresponding averages msa, msb, msc, msab, msac, msbc, msabc, and mse. If, for instance, factor A has a strong effect on the experimental observations, then msa will be relatively large.