answered prayer, bell curves, ice cream, and commodes

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>>which to me implies a Gaussian normal
distribution, yet you have a finite number of samples in your example,
and none can possibly be negative, and there is certainly an upper
bound also -- the tallest person in the sample space, so the normal
distribution is replaced by a binomial distr5ibution.  If you have an
infinite (or near infinite) number of samples, with a lower bound but
no upper bound (such as the speed of molecules in a gas), you would
use a Poisson distribution.  The computation of the first moment, or
mean (colloquialloy called the "average"), is no longer just the sum
of the samples divided by the number of samples.<<

"Up is down, left is right, and back is straight ahead"  Cain

>>Consult a good college statistics text for the details...<<

Can you say oxymoron??