## Archive for February 13, 2011

### Mean and Standard Deviation

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 ofDscore, now you square.

Sum allDscores, all scores’ share.

Now this sum, divide byN.

That’sV, the variance, then.The square root of

Vis calledSD,

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.

### Statistically Speaking…

My favorite quote from Lewis Carroll happens to be one of my favorite quotes:

If you want to inspire confidence, give plenty of statistics. It does not matter that they should be accurate, or even intelligible, as long as there is enough of them.

Here are a few statistical facts worth noting:

One of every four mathy folks suffers from mental illness. Now, think of three calculating friends. If they’re okay, then it’s you.

Fifty percent of Americans have an understanding of statistics that is below average.

69.8724% of all statistics reflect an unjustified level of precision, and 83.85% of all statistics are made up on the spot.

There are two kinds of statistics — the kind you look up, and the kind you make up.

There are three kinds of statisticians — normal, deviant, and skew.