John Poole <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>...
> In a lengthy list of measures (which are all in the same units), I am
> reporting both the Mean and the Median because some of the measures
> have a skewed distribution and others do not (I might also list the
> skewness and kurtosis, but that may be overkill). To index the
> dispersion of each measure, I am including the Standard Deviation
> (which seems most relevant in relation to the Mean) but am wondering
> what is best to use in relation to the Median.

If your data is x1,x2,...,xn with mean m, then the SD is the square
root of the mean of (x1-m)^2,(x2-m)^2,...,(xn-m)^2. It takes this form
for computational reasons, but in principle you can think of it as the
mean of |x1-m|,|x2-m|,...,|xn-m|.

So if the median in M, the analog would be to look at the median of
|x1-M|,|x2-M|,...,|xn-M|. Whether or not anyone actually uses this, I
don't know.
.
.
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