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by rsaarelm
4867 days ago
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I'm talking about the initial standardization of the test, where they determine which results correspond to which test scores by taking the results of an initial population and fitting it on a mean 100, SD 15 normal distribution: http://www.americanscientist.org/issues/id.881,y.0,no.,conte... Some scoring systems use an initial standardization where the standard deviation is 15 points, others use 24 points, so the same test performance can get you IQ 115 or IQ 124 depending on whose test you take. |
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Unless, of course, different groups of testers are using different assumptions, but without being driven by the analysis of the largest possible collection of standardized test scores. If so, it casts IQ testing into doubt as a reliable tool.
Evidence for this being a settled issue is the fact that workers in this field report a gradual increase in IQ over the decades:
http://en.wikipedia.org/wiki/Flynn_effect
If mean IQ really was adjusted to agree with current test scores, the mean would always be 100, regardless of test score changes over time.
> Some scoring systems use an initial standardization where the standard deviation is 15 points, others use 24 points, so the same test performance can get you IQ 115 or IQ 124 depending on whose test you take. [ephasis added]
The conclusion is still false -- the tests itself doesn't change, only the scoring assumptions. Those who assume σ = 15 could acquire the tests from those who assume σ = 24 and add them to their own dataset, and vice versa. Also, I have to say, either the standard deviation can't change the test scores, or the test scores have no meaning.
One more thing -- the standard deviation shouldn't be an assumption, with one group arbitrary choosing 15 and another choosing 24. The value should be derived from a large set of test scores, not a committee casting a vote.
Your argument seems to be that one's IQ score depends on the population result, along with some arbitrary assumptions like σ = 15 or σ = 24. But that's the reverse of normal statistical practice, in which the mean and standard deviation derive from test scores, not the other way around.
Obviously I'm not doubting that what you say may be so, only that it shouldn't be so -- the standard deviation shouldn't be based on anything but the analysis of a large set of standardized test scores.