The biologist: "Look! There's a herd of zebras! And there, in the middle: a white zebra! It's fantastic! There are white zebras! We'll be famous!"
The statistician: "It's not significant. We only know there's one white zebra."
The mathematician: "Actually, we know there exists a zebra which is white on one side."
The computer scientist: "Oh no! A special case!"
The engineer is first, and the basket is set ablaze. The engineer immediately jumps up, grabs the bucket of water and dashes the entire thing onto the fire, flooding the entire room and extinguishing the fire.
The physicist is next. The basket ignites, the physicist quickly calculates exactly how much water is required to extinguish the flames and pours exactly that amount, neatly extinguishing the flames.
The mathematician next. The basket blazes up, the mathematician calculates exactly how much water is required to put out the fire, and then walks out of the room.
The statistician is last. The basket is ignited. He grabs the bucket, pours half on one side, half on the other, and announces, "It's out."
The physicist says, "I know what to do! We must cool down the materials until their temperature is lower than the ignition temperature and then the fire will go out."
The chemist says, "No! No! I know what to do! We must cut off the supply of oxygen so that the fire will go out due to lack of one of the reactants."
While the physicist and chemist debate what course to take, they both are alarmed to see the statistician running around the room starting other fires. They both scream, "What are you doing?"
To which the statistician replies, "Trying to get an adequate sample size."
Mathematics is the systematic misuse of a nomenclature developed for that specific purpose. (Poul-Henning Kamp, [email protected])
"The group was alarmed to find that if you are a labourer, cleaner or dock worker, you are twice as likely to die than a member of the professional classes." (The Sunday Times, August 31, 1980)
Statistics is the art of never having to say you're wrong. Variance is what any two statisticians are at. (C. J. Bradfield, [email protected])
97.3% of all statistics are made up.
It's like the tale of the roadside merchant who was asked to explain how he could sell rabbit sandwiches so cheap. "Well," he explained, "I have to put some horse-meat in too. But I mix them 50:50. One horse, one rabbit." (Darrel Huff, How to Lie with Statistics)
Are statisticians normal?
Smoking is a leading cause of statistics. [Jascha Franklin-Hodge's ([email protected]) List of Taglines]
43% of all statistics are worthless. [Jascha Franklin-Hodge's ([email protected]) List of Taglines]
"There are lies, damned lies, and statistics." (Mark Twain)
3 out of 4 Americans make up 75% of the population. [Jascha Franklin-Hodge's ([email protected]) List of Taglines]
Death is 99 per cent fatal to laboratory rats. [Jascha Franklin-Hodge's ([email protected]) List of Taglines]
A statistician is a person who draws a mathematically precise line from an unwarranted assumption to a foregone conclusion.
A statistician can have his head in an oven and his feet in ice, and he will say that on the average he feels fine.
Statistician: Someone who doesn't have the personality to be an accountant. (Kirk Lindberg, [email protected])
Did you hear about the statistician that couldn't get laid? He decided a simulation was good enough.
80% of all statistics quoted to prove a point are made up on the spot. (Jody Levine, [email protected])
Fett's Law: Never replicate a successful experiment. (Prasad, [email protected])
Statisticians do it when it counts.
Statisticians do it with 95% confidence.
Statisticians do it with large numbers.
Statisticians do it with only a 5% chance of being rejected.
Statisticians do it with two-tailed t-tests.
Statisticians do it. After all, it's only normal.
Statisticians probably do it.
(Chris Morton, [email protected])
(5000 x 1 + 56,995,000 x 2)/57,000,000 = 1.9999123.Since most people have two legs...
"He's a statistician," replied Lamia, with an annoying sense of being on the defensive.
Lady Nuttal was obviously taken aback. It had not occurred to her that statisticians entered into normal social relationships. The species, she would have surmised, was perpetuated in some collateral manner, like mules.
"But Aunt Sara, it's a very interesting profession," said Lamia warmly.
"I don't doubt it," said her aunt, who obviously doubted it very much. "To express anything important in mere figures is so plainly impossible that there must be endless scope for well-paid advice on the how to do it. But don't you think that life with a statistician would be rather, shall we say, humdrum?"
Lamia was silent. She felt reluctant to discuss the surprising depth of emotional possibility which she had discovered below Edward's numerical veneer.
"It's not the figures themselves," she said finally. "It's what you do with them that matters."
"We can't," admits Wheeler blithely. "Frankly, after the first million we stop counting, and round it up to the next million. I don't know if you've ever counted a papal flock, but, not only do they look a bit the same, they also don't keep still, what with all the bowing and crossing themselves."
"The only way you could do it accurately is by taking an aerial photograph of the crowd and handing it to the computer to work out. But then you'd get a headline saying, '1,678,163 [sic] flock to see Pope, not including 35,467 who couldn't see him,' and, believe me, nobody wants that sort of headline."
The art of big figures, avers Wheeler, lies in psychology, not statistics. The public like a figure it can admire. It likes millionaires, and million-sellers, and centuries at cricket, so Wheeler's international agency gives them the figures it wants, which involves not only rounding up but rounding down.
"In the old days people used to deal with crowds on the Isle of Wight principle--you know, they'd say that every day the population of the world increased by the number of people who could stand upright on the Isle of Wight, or the rain-forests were being decreased by an area the size of Rutland. This meant nothing. Most people had never been to the Isle of Wight for a start, and even if they had, they only had a vision of lots of Chinese standing in the grounds of the Cowes Yacht Club. And the Rutland comparison was so useless that they were driven to abolish Rutland to get rid of it.
"No, what people want is a few good millions. A hundred million, if possible. One of our inventions was street value, for instance. In the old days they used to say that police had discovered drugs in a quantity large enough to get all of Rutland stoned for a fortnight. *We* started saying that the drugs had a street value of #10 million. Absolutely meaningless, but people understand it better."
Sometimes they do get the figures spot on. "250,000 flock to see Royal two," was one of his recent headlines, and although the 250,000 was a rounded-up figure, the two was quite correct. In his palatial office he sits surrounded by relics of past headlines--a million-year-old fossil, a #500,000 Manet, a photograph of the Sultan of Brunei's #10,000,000 house--but pride of place goes to a pair of shoes framed on the wall.
"Why the shoes? Because they cost me #39.99. They serve as a reminder of mankind's other great urge, to have stupid odd figures. Strange, isn't it? They want mass demos of exactly half a million, but they also want their gramophone records to go round at thirty-three-and-a-third, forty-five and seventy-eight rpm. We have stayed in business by remembering that below a certain level people want oddity. They don't want a rocket costing #299 million and 99p, and they don't want a radio costing exactly #50."
How does he explain the times when the figures clash--when, for example, the organisers of a demo claim 250,000 but the police put it nearer 100,000?
"We provide both sets of figures; the figures the organisers want, and the figures the police want. The public believe both. If we gave the true figure, about 167,890, nobody would believe it because it doesn't sound believable."
John Wheeler's name has never become well-known, as he is a shy figure, but his firm has an annual turnover of #3 million and his eye for the right figure has made him a rich man. His greatest pleasure, however, comes from the people he meets in the counting game.
"Exactly two billion, to be precise."
(Miles Kington, writing in The Observer, November 3, 1986)
The student replies bitterly (as he is still flipping the coin), "Shhh! I am checking my answers!"
(Sunita Saini, [email protected])
This was commonly regarded
As a feat of skill and cunning.
Several
sarcastic spirits
Pointed out to him, however,
That it might be much more
useful
If he sometimes hit the target.
"Why not shoot a little
straighter
And employ a smaller sample?"
Hiawatha, who at
college
Majored in applied statistics,
Consequently felt entitled
To
instruct his fellow man
In any subject whatsoever,
Waxed exceedingly
indignant,
Talked about the law of errors,
Talked about truncated
normals,
Talked of loss of information,
Talked about his lack of
bias,
Pointed out that (in the long run)
Independent observations,
Even
though they missed the target,
Had an average point of impact
Very near
the spot he aimed at,
With the possible exception
of a set of measure
zero.
"This," they said, "was rather doubtful;
Anyway it didn't matter.
What
resulted in the long run:
Either he must hit the target
Much more often
than at present,
Or himself would have to pay for
All the arrows he had
wasted."
Hiawatha, in a temper,
Quoted parts of R. A. Fisher,
Quoted Yates and
quoted Finney,
Quoted reams of Oscar Kempthorne,
Quoted Anderson and
Bancroft
(practically in extenso)
Trying to impress upon them
That what
actually mattered
Was to estimate the error.
Several of them admitted:
"Such a thing might have its uses;
Still,"
they said, "he would do better
If he shot a little straighter."
Hiawatha, to convince them,
Organized a shooting contest.
Laid out in
the proper manner
Of designs experimental
Recommended in the
textbooks,
Mainly used for tasting tea
(but sometimes used in other
cases)
Used factorial arrangements
And the theory of Galois,
Got a
nicely balanced layout
And successfully confounded
Second order
interactions.
All the other tribal marksmen,
Ignorant benighted creatures
Of
experimental setups,
Used their time of preparation
Putting in a lot of
practice
Merely shooting at the target.
Thus it happened in the contest
That their scores were most
impressive
With one solitary exception.
This, I hate to have to say
it,
Was the score of Hiawatha,
Who as usual shot his arrows,
Shot them
with great strength and swiftness,
Managing to be unbiased,
Not however
with a salvo
Managing to hit the target.
"There!" they said to Hiawatha,
"That is what we all
expected."
Hiawatha, nothing daunted,
Called for pen and called for
paper.
But analysis of variance
Finally produced the figures
Showing
beyond all peradventure,
Everybody else was biased.
And the variance
components
Did not differ from each other's,
Or from Hiawatha's.
(This
last point, it might be mentioned,
Would have been much more convincing
If
he hadn't been compelled to
Estimate his own components
From experimental
plots on
Which the values all were missing.)
Still they couldn't understand it,
So they couldn't raise
objections.
(Which is what so often happens
With analysis of
variance.)
All the same his fellow tribesmen,
Ignorant benighted
heathens,
Took away his bow and arrows,
Said that though my
Hiawatha
Was a brilliant statistician,
He was useless as a bowman.
As
for variance components
Several of the more outspoken
Made primeval
observations
Hurtful of the finer feelings
Even of the statistician.
In a corner of the forest
Sits alone my Hiawatha
Permanently
cogitating
On the normal law of errors.
Wondering in idle moments
If
perhaps increased precision
Might perhaps be sometimes better
Even at the
cost of bias,
If one could thereby now and then
Register upon a target.
[W. E. Mientka, "Professor Leo Moser--Reflections of a Visit," American Mathematical Monthly, Vol. 79, Number 6 (June-July, 1972)]