Monday, June 2, 2014

"But the Numbers Don't Lie"

The commonplace view of scientific method is that hypotheses ("Inequality will always rise", "Inequality causes depression", "Temperatures have just shot up", "Culling badgers cures bovine TB") can only be rejected, or falsified. Experimental data is used in an attempt to "disprove" the null version of these hypotheses (that is, their converses: "Inequality isn't rising", and so on), in a fairly antiquated and hugely flawed statistical process known as "significance testing". If a significance test is positive, people not trained in statistical reasoning – newspaper columnists, Leftists with books to sell – have a tendency to start claiming that "the science has been proven."
It hasn't (even those statisticians who continue to hawk significance testing as a valid approach to induction wouldn't make that claim), and in any case, this isn't how our reasoning about the universe works.

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