Hello again,
In response to Donald Burrill I would like to clarify what I said in my
original post. I have a vector A with 102 elements. The mean of these
elements is 50. These elements all are close to 50. The variance is
~90 which is small given the magnitude of the mean. The maximum and
minimum values are also fairly close to 50. There are not any clearly
outlying observations. The distribution is symetric about the mean and
tight to the mean as well. Clearly, it is in some sense near to the
mean and not very variable. The other vector B has same n=102. It is
from a different population and I know the means of these two vectors
are not equal. Vector B has mean 0.3. It has variance that is 9. The
distribution is symetric (more or less) about the mean but the values
are very spread out and not tight around the mean. Clearly the
_variance_ of vector A is larger than the variance of B BUT I think I
am right to say that A is less variable than B.
My decision to say this is based on their graphical representations.
Maybe it is wrong to think there is a way to quantify this. Maybe this
isn't very much an issue of statistics.
Thank you again,
Sincerly,
Yorgi V.
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