The Dunning-Kruger Effect Is Autocorrelation
Very interesting article and statistical analysis, but I really don&#x27;t see how it concludes that the DK effect is wrong based on the analysis. The fact that the DK effect emerges with _completely random data_ is not surprising at all - in this case the intuitive null hypothesis would be that people are good at estimating their skill, therefore there would be strong a correlation between their performance and self-evaluation of said performance. If the data weren&#x27;t related, then this hypothesis isn&#x27;t likely, which is exactly what DK means. And indeed if you look at the plots in the article (of the completely random data), they depict a world in which people are very bad at estimating their own skill, therefore, statistically, people with lower skills tend to overestimate their skills, and experts tend to underestimate it.<p>Also wanted to point out that in general there is no issue with looking at y - x ~ x, this is called the residual plot, and is specifically used to compare an estimate of some value vs. the value itself.<p>That being said, the author seems very confident in their conclusion, and from the comments seems to have read a lot of related analyses, so I might be missing something. ¯\_(ツ)_&#x2F;¯