Mean and Standard Deviation

February 13, 2011 at 11:27 pm Leave a comment

As a follow-up to yesterday’s post, here’s a poem titled Mean and SD by Norman Chansky, professor emeritus at Temple University. Ostensibly, the poem first appeared in the Journal of Irreproducible Results, though I was unable to find an exact citation.

The mean is a measure of location,
The center of a population.
If at random a score you drew,
The mean’s the most likely score you’d view.

You can compute the mean in your slumber:
Sum the scores, and divide by the number.  
At the mean, sample scores converge;       
From the mean, these scores diverge.       
Near the mean, the scores are many.
In the tails, there are hardly any.         

But to measure a distribution’s variation,
From the mean, find each score’s deviation.
Each difference of D score, now you square.
Sum all D scores, all scores’ share.
Now this sum, divide by N.
That’s V, the variance, then.

The square root of V is called SD,
The gauge of a trait’s variability.
We’ve found two moments of a distribution,
Developed from each score’s contribution.

Picturing a universe, try to see:
Its center, the mean; its orbit, SD

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The Math Jokes 4 Mathy Folks blog is an online extension to the book Math Jokes 4 Mathy Folks. The blog contains jokes submitted by readers, new jokes discovered by the author, details about speaking appearances and workshops, and other random bits of information that might be interesting to the strange folks who like math jokes.

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