I didn't count anything. Just plotted data from the book. Read the book for details.
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You can just download the book from libgen. http://gen.lib.rus.ec/search.php?req=Human+Accomplishment&open=0&res=25&view=simple&phrase=1&column=def …
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It's unimportant what evil/wrong ideas you may be able to relate findings to (genetic fallacy).
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What assumption is that? @BodoStaron
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Not an assumption, empirical result. Look at absolute numbers. https://twitter.com/KirkegaardEmil/status/804889266161586176 … @BodoStaron
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Worse yet, R!
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No, I chose these because restructuring the data was too difficult.
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In any case, the other group is ~48% Indian (brown) ~48% Arab (light brown).
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Aha, thanks!
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Of course. When Euros failed in dark ages, not much happened elsewhere either.pic.twitter.com/w3PRLYMIGL
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Very emotional "nailing", but not very cogent.
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Or maybe: very emotional but not very nailing. :)
@HobbesianM @lizboumboum@charlesmurray
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now that looks interesting - is it on kindle?
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Seshat project people don't think too highly of that DB, not sure whether omissions make a big diffhttps://twitter.com/EALTurner/status/691961545664897025 …
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Don't think they even looked at the dataset. It wasn't released publicly until recently.
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released 22.01.2016. his tweet was 4 days later. apparently he looked at it before you
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Oh hey I made some more graphs with binomial smoothing, an animated bootstrap, and Bayesian multilevel time-series: https://www.gwern.net/Statistical%20notes#proportion-of-important-thinkers-by-global-region-over-time-in-charles-murrays-human-accomplishment …pic.twitter.com/cJmeMQKyJ4
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Also, you complain about how much of a pain it is to write JAGS models. Maybe check out brms, fairly powerful: https://cran.r-project.org/web/packages/brms/vignettes/brms_multilevel.pdf …
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I think the gains of using Bayesian models are usually ~zero, and the price in time is >0, often large. But I'll have a look again.
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