Correlation: Difference between revisions
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*{{br|The Book of Why: The New Science of Cause and Effect}} by {{author|Judea Pearl}} | |||
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Revision as of 10:22, 23 September 2019
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The idea, first articulated by statistician Karl Pearson[1], that a relationship between two variables could be characterised according to its strength and expressed in numbers.
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
References
- ↑ 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.