**Answer to ****Module
1, Exercise 1g:
**

SS Total is the sum of the squared deviations of Y scores
from the mean of Y. If SS Total was much smaller, then all of the Y values must
be close to the mean. SS Total could be much larger for several reasons: many of
the Y values could be somewhat farther from the mean, a few values, or even one
value, could be very far from the mean, or we could simply have many more Y
values. Note that a single Y value that differed from the mean by 10 points
would contribute 100 to SS Total.

There is a close relationship between SS Total and variance. An estimate of the population variance taken from a sample is calculated at the sum of the squared deviations from the mean divided by the degrees of freedom, which is (SS Total) / (n-1) for a single sample. In our example, this is 14/3 = 4.667. The standard deviation is the square root of variance = 2.16, the value shown in the applet as the std dev for the DV.