Correlation: Difference between revisions
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[[File:Quincunx.jpg|450px|thumb|center|A [[quincunx]], yesterday]]}}The idea, following from Sir Francis Galton’s experiments with a [[quincunx]] and first articulated by statistician Karl Pearson<ref>So [https://slate.com/technology/2012/10/correlation-does-not-imply-causation-how-the-internet-fell-in-love-with-a-stats-class-cliche.html Slate Magazine] argues, at any rate.</ref> that a relationship between two variables could be characterised according to its statistical strength and expressed in numbers, regardless of any perceived causal connection between them. | [[File:Quincunx.jpg|450px|thumb|center|A [[quincunx]], yesterday]]}}The idea, following from Sir Francis Galton’s experiments with a [[quincunx]] and first articulated by statistician Karl Pearson<ref>So [https://slate.com/technology/2012/10/correlation-does-not-imply-causation-how-the-internet-fell-in-love-with-a-stats-class-cliche.html Slate Magazine] argues, at any rate.</ref> that a relationship between two variables could be characterised according to its statistical strength and expressed in numbers, regardless of any perceived causal connection between them. | ||
If one can derive significance from a purely statistical correlation, without any deeper mechanical theory of the universe that might tell us ''why'', we are well on our way to an artificially intelligent future where robots can wipe elderly arses, all bankers are redundant, and it is only a matter of time before Skynet becomes self-aware and starts hunting down random skater kids from the 1990s. | If one can derive significance from a purely statistical correlation, without any deeper mechanical theory of the universe that might tell us ''why'', we are well on our way to an [[Artificial intelligence|artificially intelligent]] future where robots can wipe elderly arses, [[Rumours of our demise are greatly exaggerated - technology article|all bankers are redundant]] (good, right?), [[A World Without Work: Technology, Automation, and How We Should Respond - Book Review|so is everyone else]] (''not'' so good?) and it is only a matter of time before Skynet becomes self-aware and starts hunting down random skater kids from the 1990s. | ||
Well, in some cases you can, in some cases you can’t<ref>There are whole websites devoted to spurious correlations. Like, well, http://www.spuriouscorrelations.com.</ref> but — irony upcoming — without a sophisticated theory of ''causality'', it will be hard to tell them apart. That is to say, a bare [[correlation]] won’t tell you whether there is a causal arrow at all. much less — if there is — which way it flows. | Well, in some cases you ''can'' derive a significance, in some cases you ''can’t''<ref>There are whole websites devoted to spurious correlations. Like, well, http://www.spuriouscorrelations.com.</ref> but — irony upcoming — without a sophisticated theory of ''causality'', it will be hard to tell them apart. That is to say, a bare [[correlation]] won’t tell you whether there is a causal arrow at all. much less — if there is — which way it flows. | ||
“Correlation”<ref>“A mutual relationship or connection between two or more things.”</ref> ''ought to be'' a synonym for “coincidence”<ref>“A remarkable concurrence of events or circumstances without apparent causal connection,” sayeth the Google.</ref> though in its more fashionable usages, especially among [[big data]] freaks, this tends to be get — well — ''buried'' in the [[signal-to-noise ratio|noise]]. There may be something profound, reflexive and ironic about this, but it's too early in the morning to figure out out. At any rate, the more data you have the, the more noise to the [[signal-to-noise ratio|signal]], and the more chanting “correlation does not imply causation” in a sing-song voice whenever anyone cites a correlation will annoy the ''hell'' out of [[big data]] freaks — which ought to be all the reason you need to do it. | “Correlation”<ref>“A mutual relationship or connection between two or more things.”</ref> ''ought to be'' a synonym for “coincidence”<ref>“A remarkable concurrence of events or circumstances without apparent causal connection,” sayeth the Google.</ref> though in its more fashionable usages, especially among [[big data]] freaks, this tends to be get — well — ''buried'' in the [[signal-to-noise ratio|noise]]. There may be something profound, reflexive and ironic about this, but it's too early in the morning to figure out out. At any rate, the more data you have the, the more noise to the [[signal-to-noise ratio|signal]], and the more chanting “correlation does not imply causation” in a sing-song voice whenever anyone cites a correlation will annoy the ''hell'' out of [[big data]] freaks — which ought to be all the reason you need to do it. | ||
Revision as of 11:37, 16 October 2020
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The idea, following from Sir Francis Galton’s experiments with a quincunx and first articulated by statistician Karl Pearson[1] that a relationship between two variables could be characterised according to its statistical strength and expressed in numbers, regardless of any perceived causal connection between them.
If one can derive significance from a purely statistical correlation, without any deeper mechanical theory of the universe that might tell us why, we are well on our way to an artificially intelligent future where robots can wipe elderly arses, all bankers are redundant (good, right?), so is everyone else (not so good?) and it is only a matter of time before Skynet becomes self-aware and starts hunting down random skater kids from the 1990s.
Well, in some cases you can derive a significance, in some cases you can’t[2] but — irony upcoming — without a sophisticated theory of causality, it will be hard to tell them apart. That is to say, a bare correlation won’t tell you whether there is a causal arrow at all. much less — if there is — which way it flows.
“Correlation”[3] ought to be a synonym for “coincidence”[4] though in its more fashionable usages, especially among big data freaks, this tends to be get — well — buried in the noise. There may be something profound, reflexive and ironic about this, but it's too early in the morning to figure out out. At any rate, the more data you have the, the more noise to the signal, and the more chanting “correlation does not imply causation” in a sing-song voice whenever anyone cites a correlation will annoy the hell out of big data freaks — which ought to be all the reason you need to do it.
Correlation and causation
Now it is true that correlation doesn’t imply causation, but it doesn’t rule it out either. And it is certainly true that a lack of correlation does imply a lack of causation.
All other things being equal, a correlation is more likely to evidence a causation than a lack of correlation, right? This is one of those logical canards, as Monty Python put it, “universal affirmatives can only be partially converted: all of Alma Cogan is dead, but only some of the class of dead people are Alma Cogan.”
See also
- In God we trust, all others must bring data
- Contractual causation
- The Book of Why: The New Science of Cause and Effect by Judea Pearl
References
- ↑ So Slate Magazine argues, at any rate.
- ↑ There are whole websites devoted to spurious correlations. Like, well, http://www.spuriouscorrelations.com.
- ↑ “A mutual relationship or connection between two or more things.”
- ↑ “A remarkable concurrence of events or circumstances without apparent causal connection,” sayeth the Google.