- “All models are wrong, but some are useful”
- “Statisticians, like artists, have the bad habit of falling in love with their models”.
Twyman’s Law and Corollaries
- “If it looks interesting, it must be wrong”
- De Veaux’s Corollary 1 to Twyman’s Law: “If it’s perfect, it’s wrong”
- De Veaux’s Corollary 2 to Twyman’s Law: “If it isn’t wrong, you probably knew it already
"All models should be as simple as possible but no simpler than necessary"
By simply googling the website, I can find some additional quotes/axioms:
- “Data mining is the discovery of interesting, unexpected, or valuable structures in large datasets”
- "If it’s interesting or unusual it’s probably wrong"
- “All models are wrong, some are useful”
- “If we torture the data long enough, they will confess”
- "What’s the difference between a biostatistician and a physician? A physician makes an analysis of a complex illness whereas a biostatistician makes you ill with a complex analysis."
Twyman's Law (created by Tony Twyman the expert UK based media analyst) states that "If a thing surprises you, it's wrong" Has anyone investigated to what extent the reported loss is real or a research arifact?
There is a rule in market research called Twyman’s law: “anything surprising or interesting is probably wrong”. While not going that far, one should be always advised that if you find a poll result that seems somewhat counter-intuitive, that seems to have no obvious explanation, treat it with caution until other polls support the findings. Statistically there is no more reason for this poll to be wrong than the last poll or the poll before that, and we may indeed find that this is a genuine trend and everyone starts showing the Tories down, but it is a bit odd.
Jim's favorite quotes
Imaging results about catoon statistics from google
Use humor to teach statistics
Collection of statistics joke and humor