Okay, so the IQ tweet storm has been turned into a Medium post.https://medium.com/incerto/iq-is-largely-a-pseudoscientific-swindle-f131c101ba39 …
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He seems to focus on this graphic a lot, but this scatterplot looks odd. It looks odd because n looks like it's at least a couple hundred, but all the IQ scores are contained within 2sigma of the national mean.pic.twitter.com/rRPT6QeZbF
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But it's also the case that the average IQ of this data set is well above national mean. Doesn't this seem... fishy?
@pnin1957 or@KirkegaardEmil ?3 replies 0 retweets 4 likesShow this thread -
Should be somewhat above the mean, SAT test takers are self selecting. Dunno how high but 110 (eyeball average) doesn't seem wildly implausible.
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Yeah, mean IQ ~110 for people who take the SAT is reasonable (via selection bias). But with n ~= 200 (eyeballed) why is there no one above 130 IQ? I mean, if the sample mean is .6sigma above the population mean, shouldn't we expect more scores above 130?
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The range restriction is bizarre, yes.
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Presumably he used data based on a test with a low ceiling, e.g. WORDSUM.
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I'd guess it's based on one of the NLSY samples and the AFQT. The regression of AFQT on SAT looks as below in the NLSY79. The slope levels off at the high end, but I'd think it's b/c the AFQT lacks discrimination there; in military use, everyone scoring >122 gets the same score.pic.twitter.com/N6NyXSfIat
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Looking at this plot again, it looks like there is a 145 ceiling affect which is bending the top tail down. But also looks heteroskedastic (noisier at the top). Suppose it is; how should I roll that into my understanding? Should I do regressions on the logged variables instead?
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It means that your prediction intervals will be larger at the high end. It can also result from the test properties, as pnin says. Most tests have bad reliability in high range because of little practical relevance and SLODR effect.
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I'm surprised you would suggest that in the high range tests have "little practical relevance."
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