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#1
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The only thing similar to it that I can think of is the likelihood ratio test to compare "full" and "reduced" models in statistics - adding an extra explanatory variable always gives you a better fit even if the extra variable is meaningless, so you have to prove the extra variable has improved the fit more than would be expected by chance.
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#2
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I have no understanding of full and reduced models in statistics, but what you've said sounds both right and wrong, if you see what I mean - right in that it sounds analagous, wrong in that the extra information is making the proposition likelier rather than less likely.
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#3
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What, if any, is the relationship between Ockham's Razor and Sklansky's "Coincidence Theory"?
I found the two to be quite similar in nature. |
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