This VI computes the total sum of squares, tss, which is a measure of the total variation of the data from the overall population mean.
tss consists of two parts: ssa, a measure of variation attributed to the factor, and sse, a measure of variation attributed to random fluctuation. In other words,
tss = ssa + sse.
The VI computes the two mean square quantities msa and mse from ssa and sse by dividing ssa and sse by their own degrees of freedom. The larger msa is relative to mse, the more significant effect the factor has on the experimental outcome.
In particular, if the null hypothesis is true, then the ratio f, f = msa/mse, is taken from an F distribution with k 1 and n k degrees of freedom, from which you can calculate probabilities. Given a particular f, sigA is the probability that you get a value larger than f when sampling from this distribution.