What is your favorite statistical quote?
This is community wiki, so please one quote per answer.
Figures don't lie, but liars do figure
"Million to one chances crop up nine times out of ten."
This is unlikely to be a popular quote, but anyway,
If your experiment needs statistics, you ought to have done a better experiment.
The plural of anecdote is not data.
-- Roger Brinner
(in the context of Anecdotal_evidence)
Those who ignore Statistics are condemned to reinvent it.
-- Brad Efron
…the statistician knows…that in nature there never was a normal distribution, there never was a straight line, yet with normal and linear assumptions, known to be false, he can often derive results which match, to a useful approximation, those found in the real world.
George Box (JASA, 1976, Vol. 71, 791-799)
The death of one man is a tragedy. The death of millions is a statistic.
-- Kurt Tucholsky, in: Französischer Witz, 1925
"It is easy to lie with statistics. It is hard to tell the truth without statistics." - Andrejs Dunkels
"The first time I was in a statistics course, I was there to teach it"
John Tukey (link)
"To find out what happens when you change something, it is necessary to change it.”
Box, Hunter, and Hunter, Statistics for Experimenters (1978).
I keep saying that the sexy job in the next 10 years will be statisticians. And I'm not kidding.
The greatest value of a picture is when it forces us to notice what we never expected to see.
-- John Tukey
There are three kinds of lies: lies, damned lies, and statistics.
We are drowning in information and starving for knowledge.
Rutherford D. Roger
60% of the time, it works every time.
"The Central Limit Theorem is about the journey and the Strong Law of Large Numbers is about the destination." stats.SE user cardinal in a comment on this question
While the individual man is an insoluble puzzle, in the aggregate he becomes a mathematical certainty. You can, for example, never foretell what any one man will be up to, but you can say with precision what an average number will be up to. Individuals vary, but percentages remain constant. So says the statistician.
Arthur Conan Doyle
The statistician cannot evade the responsibility for understanding the process he applies or recommends.
-– Sir Ronald A. Fisher
It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.
Mark Twain (okay, so he's not a statistician)
This one is brand new, and Allen Wilcox is an epidemiologist, not a statistician, but whatever, I'm running with it.
Data do not speak for themselves - they need context, and they need skeptical evaluation
Correlation doesn’t imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there’.
"Extraordinary claims demand extraordinary evidence."
Often attributed to Carl Sagan, but he was paraphrasing sceptic Marcello Truzzi. Doubtless the concept is even more ancient.
David Hume said, "A wise man, therefore, proportions his belief to the evidence".
One could argue this is not a quote about statistics. However, applied statistics is ultimately in the business of evaluating the quality of evidence for or against some proposition.
My thesis is simply this: probability does not exist. - Bruno de Finetti
If I can't picture it, I can't understand it.
I acknowledge that Einstein wasn't a statistician. However, Michael Friendly uses this quote in arguing for a greater role for visualizations in data analysis. I share that goal, and I think the quote works nicely.
An ecologist is a statistician who likes to be outside.
-- apparently a good friend of Murray Cooper.
The primary product of a research inquiry is one or more measures of effect size, not p values.
Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45, 1304-1312.
The Earth is round. p < .05
When I see articles with lots of significance tests, I say that the statisticians are p-ing on the research.
Herman Friedmann (by recollection, he said this in class)
May I add this one, because I like Jan's contributions to psychometrics and statistics...
Causal interpretation of the results of regression analysis of observational data is a risky business. The responsibility rests entirely on the shoulders of the researcher, because the shoulders of the statistical technique cannot carry such strong inferences.
Jan de Leeuw, homepage
I just can't help myself, this is a provocative quote from E. T. Jaynes:
Many of us have already explored the road you are following, and we know what you will find at the end of it. It doesn't matter how many new words you drag into the discussion to avoid having to utter the word 'probability' in a sense different from frequency: likelihood, confidence, significance, propensity, support, credibility, acceptability, indifference, consonance, tenability; and so on, until the resources of the good Dr Roget are exhausted. All of these are attempts to represent degrees of plausibility by real numbers, and they are covered automatically by Cox's theorems. It doesn't matter which approach you happen to like philosophically; by the time you have made your methods fully consistent, you will be forced, kicking and screaming, back to the ones given by Laplace. Until you have achieved mathematical equivalence with Laplace's methods, it will be possible, by looking in specific problems with Galileo's magnification, to exhibit the defects in your methods.
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