What is your favorite statistical quote?
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Found in Warning Signs in Experimental Design and Interpretation by Peter Norvig
Most of the time, when you get an amazing, counterintuitive result, it means you have screwed up the experiment
in the sense of
Extraordinary claims require extraordinary evidence
which is based on a similar quote by Pierre Laplace
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.
preamble: There is even a class of user now days who sees the signiﬁcance stars rather like the gold stars my grandson sometimes gets on his homework:
Three solid gold (significance) stars on the main effects will do very nicely, thank you, and if there are a few little stars here and there on the interactions, so much the better!
Don't think -- use the computer.
Attributed ("tongue in cheek," just to make sure we understand the intent) to "G. Dyke." Quoted in Phillip I. Good and James W. Hardin, Common Errors in Statistics: see the very first page of Part I.
A "G. Dyke" is cited in the bibliography as the author of How to avoid bad statistics. Field Crops Res. 1997; 51: 165-197. This apparently is George Dyke, who later in the book is quoted more at length:
The availability of 'user-friendly' statistical software has caused authors to become increasingly careless about the logic of interpreting their results, and to rely uncritically on computer output, often using the 'default option' when something a little different (usually, but not always, a little more complicated) is correct, or at least more appropriate.
[Cited on pp 71-72 in the first edition, 2003.]
A related quotation graces the beginning of Chapter 7:
Cut out the appropriate part of the computer output and paste it onto the draft of the paper.
"Statistics is exciting because you get to play with others' data while telling them their research is crap."
Stephen J. Senn (Source)
At their best, graphics are instruments for reasoning.
Edward Tufte, www.edwardtufte.com
"After 17 years of interacting with physicians, I have come to realize that many of them are adherents of a religion they call Statistics... Like any good religion, it involves vague mysteries capable of contradictory and irrational interpretation. It has a priesthood and a class of mendicant friars. And it provides Salvation: Proper invocation of the religious dogmas of Statistics will result in publication in prestigious journals."
With three constants, I can fit a dog. With four, I can make it bark.
Attributed to William Reifsnyder, in a personal communication to me. Unfortunately I can't find a reference on the 'web.
One sees, from this Essay, that the theory of probabilities is basically just common sense reduced to calculus; it makes one appreciate with exactness that which accurate minds feel with a sort of instinct, often without being able to account for it.
Another one from Laplace
“There are two things you are better off not watching in the making: sausages and econometric estimates.” - Edward Leamer
The quote comes from:
Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
And he also says it, in spoken word, on this EconTalk podcast hosted by Russ Roberts.