When your data totally backs your thesis.
@josephbenton that means r2 is 0.0144. the best case scenario for this line is barely over 1% of variance lmao
@josephbenton That, uh.
That looks like sample size bias to me.
Either that or an uncovered pollock original
Here's the full thread if you want to see the full horror: https://twitter.com/baumard_nicolas/status/1308715609795039232
@josephbenton @paladin @RussellsBarbershopQuartet "Our results thus show that trustworthiness in portraits increased over the period 1500–2000 paralleling the decline of interpersonal violence and the rise of democratic values observed in Western Europe" how can you just state that seriously, the heck is trustworthiness and oh my god this is bad. This is truly bad
@josephbenton @paladin @RussellsBarbershopQuartet what punches me in the face is the lack of reflexiveness on how their metric is defined (how about non white people, or disabled people), their spurious correlation and how they absolutely do not care about the consequences of their work on a surveillance capitalism setting where facial recognition is the big hyped stuff
@paladin @josephbenton right, but if you do that, then you'd have to multivariate math, and no one wants to see that bc if you're getting fucking r2 = 0.0144 with this many participants, you'd need so so many more to get the appropriate statistical power for what is, again, demonstrably barely even a drop in the bucket
@josephbenton I like the error indicators on the regression because they don't seem to have any correlation to the data or the regression
@josephbenton those correlation coefficients sure are doing a lot of work to try to make their case.
@josephbenton Almost got fooled by the trendline apparently arbitrarily drawn through a meaningless field of data points.
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