Adjusted stats - how valuable?
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10-24-2012, 12:43 PM
Join Date: Apr 2007
Originally Posted by
Look closely at your graph. It follows the raw data at the extremes of course. First it clearly decreases compared to the raw data. That means your data takes on smaller values. Next it clearly increases compared to the raw data. That means your data takes on bigger values. Then it decreases compared to the raw data. That means your data takes on smaller values. A bell curve. Lower values then higher values then lower values.
Its fricken obvious man. This is the kind of behaviour one would expect when applying a function based on a bell curve ( normalization) to another curve. You equation is based on average scoring
as if the distribution of goals amongst the players was uniform
. I've already shown that it isn't. I think most of us including you knew that already without math.
. There is no normalization. Unless you're mathematically illiterate, you can easily convince yourself by looking at the damn formula.
Adj(1952-53) = Raw(1952-53) * F(1952-53)
Where's the "normalization" here?
Any shape in the original distribution will be reproduced in the adjusted distribution. There is no bell curve. If Iain had 2 graphs, one with the original data and the original "bins" (16-19 etc), and a 2nd one with adjusted data and scaled bins (16*F to 19*F etc), your bell curve hallucination would vanish.
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