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Notes -
I think the point was something else. Imagine another test where people threw a dice and then they estimated what their dice throw was. Of course people who threw 6 could only underestimate or be correct and people who threw 1 could only be correct or overestimate.
So even if both the result and estimation was random, then you would reproduce Duning-Kruger effect due to autocorrelation. Result of “over/underestimation” is dependent and correlated to the measure you over/underestimate against which is also a variable. The correct answer is just that this is stupid statistical artefact.
Kinky.
Avoid low-effort posts, please.
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In that case I certainly did not get that impression from the blogpost, and I don't think this has anything to do with "autocorrelation" as much as it has to do with the data being bounded, which I think is another argument entirely. Incidentally I think the bounded-data explanation, which seems the most obvious one to me (along with other ones like the better-than-average effect and simple regression to the mean), are much more convincing than wrangling about autocorrelation. It's also using "autocorrelation" in a weird way.
I remain of the opinion that DKE is probably artefactual or minor at best, but the blog is still either poorly written or wrong.
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