161–170 of 308 posts
Yeah, this makes sense to me. Imagine in the Dunning-Kruger chart the second plot (perceived ability) was a horizontal line at 70, which is not true but not far off from the real results. Now imagine I told you "did you know that, regardless of their actual score, everyone thought they got a 70?" That's a surprising fact.
Beyond the validity of the statistical methods used.. can someone clarify what is the actual hypothesis we are debating about competence? And what does each article propose? My understanding is that the hypothesis is "Those who are incompetent overestimate themselves, and experts underestimate themselves". DK says: True DK is Autocorrelation says: ??? "I cant let go..." says: True? HN says: also True? Is there really…
I hate it when people are "solely2 using statistics, and other first-principle thinking approaches, to understand well researched and documented topics. And I hate it if people use solely statistics to criticize research without considering the other aspects of it. Does it mean the DK effect can be discarded or not? I don't know, I think some disagreement over the statistical methods is not enough to come to any conclusion.
Attacking the Dunning-Kruger study only on statistical grounds looks like aprime example of the DK effect in itself...
The conclusion in the article: > Why so angry? I know I’ve taken this far too personally. I have no illusions that everything I read online should be correct, or about people’s susceptibility to a strong rhetoric cleverly bashing conventional science, even in great communities such as HN. But frankly, for the last few years, the world seems to be accelerating the rate at which it’s going crazy, and it feels to me a l…
Behavioural science is a pretty new field, its pretty easy to get abberant results or manipulate the results to show 'something' statistically. Many findings in earlier papers could not be replicated, or had applied statistics incorrectly, or showed different results when research participants were not white college kids.
This is a whole other problem within academia, the pressure to publish something even when there is nothing and perceived legitimacy based on the number of citations a paper has. My professor always said don't look at the number of citations, understand the method and the rebuttal, there were numerous low citation but solid papers showing flaws in famous ones but everyone who isn't deep into the subject holds the original assertion to be legitimate because its "famous"
Earlier quoted context omitted.
"Most believe themselves 'above average' at most things."
Most people have an above-average number of legs. There's really no contradiction there; all it takes is for there to be a couple low scores pulling the average down.
The arithmetic mean and the median are both averages, but the upthread comment was about the median and yours about the arithmetic mean.
> There's really no contradiction there; all it takes is for there to be a couple low scores pulling the average down.
Well, no, when what you are estimating is relative performance by score percentiles, and people's self evaluation is biased toward the 70th percentile, that's not what is happening.
I feel like this article is severely over-complicating the analysis. Looking at the original blog post [1], their key claim appears to be that "random data produces the same curves as the DK effect, so the DK effect is a statistical artifact". However, by "random data", the original blog means people and their self-assessments are completely independent! In fact, this is exactly what the DK effect is saying -- people…
The conclusion in the article: > Why so angry? I know I’ve taken this far too personally. I have no illusions that everything I read online should be correct, or about people’s susceptibility to a strong rhetoric cleverly bashing conventional science, even in great communities such as HN. But frankly, for the last few years, the world seems to be accelerating the rate at which it’s going crazy, and it feels to me a l…
> The anti-intellectual, anti-scientific streak in many poor analyses claiming to debunk some scientific research is deeply concerning in our society. People endlessly reference the Dunning-Kruger effect as a meme, without ever having read the paper, let alone having checked its methods. You don't seem to have a problem with that. On the other hand, after seeing an article that uses essentially statistical arguments…
What's more harmful to medicine: a fashionably non-expert contrarian who doesn't understand the appropriate null hypothesis making a superficially plausible statistical argument that actually the trials suggest the drug is harmful to wide acclaim from laymen, or people casually referencing or even being administered the drug without reading the original trial writeups for themselves?
> “Never assume dependence” gets so ingrained that people stubbornly hold on to the argument in the face of all the common sense I can conjure. If you still disagree that assuming dependence makes more sense in this case, I guess our worldviews are so different we can’t really have a meaningful discussion.
Hypothesis testing is concerned with minimization of Type I and Type II errors. In the Neyman-Pearson framework this calls for specific choice of the null hypothesis. Of course nothing prevents you to define the sets for H0 and H1 as arbitrarily as you want as long as you can mathematically justify your results.
It seems like the author fundamentally misunderstands the basics of statistics.
One of the best commentaries on DK is Tal Yarkoni’s, and he came to the (perhaps similar?) conclusion that DK is probably regression to the mean. https://www.talyarkoni.org/blog/2010/07/07/what-the-dunning-... It bugs me that DK reached popular consciousness and get misinterpreted and misused more often than not. For one, the paper shows a positive correlation between confidence and skill. The paper is very clearly l…
Put differently, if everyone's estimate was exactly the mean, you'd still see a "DK effect".
Earlier quoted context omitted.
Let's not forget though that a great deal of "science" is in fact trash[1]. The problem isn't really people being anti-science or pro-science. The problem is science being done poorly, whether by scientists in the credentialed sense, or amateurs. There is no pat "trust science more" or "trust amateurs less" answer here. The actual answer is that if you want to understand research, you need to actually understand math…
part of the issue is that producing shit research cost very little, and debunking shit research cost a lot. just pick up one of the many "x reasons why earth is not a sphere" videos, some are pretty easy to debunk, but other require to understand i.e. potential fields (if earth is round why don't train engineer take into account curvature when laying tracks and variations thereof)
A theory ought to be able to answer questions like “Why don’t train engineers take the curvature of the Earth into account?”
The problem is when someone comes along and thinks an unanswered question (or even just someone not knowing the answer off the top of their head) proves a theory is completely false (or worse, proves their favorite theory correct). (And to even believe the Earth is flat is to be a conspiracy theorist so in this particular case no prove will ever suffice anyway.)