Comments on: Beware Summary Statistics

By: n/a

n/a — Mon, 01 Jun 2015 15:45:29 +0000

That’s like saying coral it’s the driest life I the ocean.

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By: Links for May 2015 - foreXiv

Links for May 2015 - foreXiv — Sun, 31 May 2015 21:42:33 +0000

[…] Anscombe’s quartet illustrates the limitations of common statistics. (H/t eric.) […]

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By: Harald K

Harald K — Fri, 29 May 2015 11:19:15 +0000

“In other words, you’re saying low IQ might be a necessary but not sufficient condition for criminality?”

Remember, “criminality” in this context specifically means getting convicted of a crime at least twice between age 16 and 20 or so. In peaceful Denmark, in the mid-1960s. Yes, it’s not very surprising that low IQ would be a “necessary” condition to be that extreme (necessary in quotes because we don’t know about causality here – there could be things that contribute both to low IQ scores and criminality, like neurological damage, childhood abuse, head trauma etc.)

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By: Emil Kirkegaard

Emil Kirkegaard — Fri, 29 May 2015 09:41:05 +0000

To anyone wondering whether this is wrong, yes. Just read the third appendix for The Bell Curve. The book can easily be found on libgen.

TL;DR It is similar to other IQ tests regarding internal structure and test items. It shows strong correlations to other IQ tests.

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By: Emil Kirkegaard

Emil Kirkegaard — Fri, 29 May 2015 09:09:21 +0000

The testing age is 18 for conscription (forsvarets dag/sessionsprøven).

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By: Emil Kirkegaard

Emil Kirkegaard — Fri, 29 May 2015 08:36:49 +0000

Regarding the first, be sure to read this paper too:
Ferguson, C. J. (2009). Is psychological research really as good as medical research? Effect size comparisons between psychology and medicine. Review of General Psychology, 13(2), 130.

TL;DR sometimes psych correlation sizes have been compared to medicine. These comparisons often show that psych effects are strong compared to medicine. However, due to the very low base rate of some medical problems, the correlations are ‘artificially’ small. Correct for that and you see large effects. Great paper.

Concerning the interpretation of small to medium correlations and grouped data, the best paper to read is this one:
Lubinski, D., & Humphreys, L. G. (1996). Seeing the forest from the trees: When predicting the behavior or status of groups, correlate means. Psychology, Public Policy, and Law, 2(2), 363.

Great paper, very undercited IMO.

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By: Some musings on statistics | Jacob Silterra

Some musings on statistics | Jacob Silterra — Thu, 28 May 2015 04:01:47 +0000

[…] had a pretty interesting post entitle “Beware of Summary Statistics“, showing how they can be misleading. This isn’t exactly new, there are famous examples […]

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By: Ian James

Ian James — Sun, 24 May 2015 20:38:42 +0000

Here all crime is committed by low IQ individuals, but the correlation between IQ and crime is still very low, r = 0.16. The reason is simple: very few people, including very few low-IQ people, commit crimes. r is kind of a mishmash of p(low IQ|criminal) and p(criminal|low IQ), and the latter may be very low even when all criminals are from the lower end of the spectrum.

In other words, you’re saying low IQ might be a necessary but not sufficient condition for criminality? And in general, small correlations between A and B can’t rule out the possibility that A is a necessary but not sufficient condition for B?

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By: fwhagdsd

fwhagdsd — Sat, 23 May 2015 18:42:40 +0000

Statistical analysis brain modules should be required for all public school students.

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By: Douglas Knight

Douglas Knight — Sat, 23 May 2015 06:13:05 +0000

My NLSY example is mistaken. I had restricted to individuals with positive income. For them, the correlation between IQ and income is 0.44, pretty much the same as the correlation between IQ and log income, 0.47. If we include incomes with zero income, the linear correlation stays the same, but the correlations between IQ and log1p or inverse hyperbolic sine is 0.34 and 0.33, respectively. The loss on transformation is comparable to the loss in the artificial example.

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