Mean Square (MS) is also called variance; approximated by the sum of squares (SS) divided by the degress of freedom (i.e., n-1); the MSE from the empty model can be thought of as roughly the average squared deviation.
SS Total is the amount of error revealed by the empty model (the mean); it is the total area of the squared residuals based on the distance of each score from the mean.
The xpnorm() function will generate the probability and z-score for a value (X) based on the mathematical function for a normal distribution. It can do this with just three pieces of information: the border you are interested in, and the mean and ...