Factoring (Possible) Effect of Dunning-Kruger.

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Discussion Overview

The discussion revolves around the potential influence of the Dunning-Kruger effect on the correlation between control measures and perceived errors in a given context. Participants explore how to account for this effect in order to achieve a more realistic expectation of error, given the available data on perceived errors and control measures.

Discussion Character

  • Exploratory
  • Debate/contested
  • Technical explanation

Main Points Raised

  • One participant suggests that the low perceived error may be explained by the Dunning-Kruger effect and seeks methods to factor this into error estimation.
  • Another participant questions the utility of the analysis without data on actual errors, emphasizing the need for comparison between actual and perceived errors.
  • A third participant reiterates the importance of having actual error data to derive useful insights and requests more details about the available data.
  • A later reply clarifies that the original poster does not have actual error data and is instead looking for ways to estimate possible errors based on perceived data and the Dunning-Kruger effect.
  • One participant concludes that without a study to determine the strength of the Dunning-Kruger effect in the specific context, it is difficult to make reliable estimates regarding actual errors.

Areas of Agreement / Disagreement

Participants generally agree that the lack of actual error data limits the analysis. However, there is no consensus on how to proceed with the estimation of errors based solely on perceived data and the Dunning-Kruger effect.

Contextual Notes

The discussion highlights limitations related to the absence of actual error data and the need for a study to assess the strength of the Dunning-Kruger effect in the specific setup being analyzed.

WWGD
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Hi All, I am looking at some data regarding correlation between control measures and (perceived)errors at
a given position. The level of error seems , intuitively, suspiciously low. I suspect the low perceived error may
be at least partially explained by the Dunning Kruger effect:
https://en.wikipedia.org/wiki/Dunning–Kruger_effect

Does anyone know of anyway of factoring the effects of Dunning-Kruger to come up with a more realistic
expectation of error given control? We have a measure of Control from 0-5, same scale for error(both scales are linear; control goes from high to low, error goes from low to high: control near 5 is high, error near 5 is low) . Say a an input of control is 1 , a low measure, and the perceived error at that level is 4. Can I make a more accurate estimate of error by factoring out effects of Dunning-Kruger?
Thanks.
 
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WWGD said:
Hi All, I am looking at some data regarding correlation between control measures and (perceived)errors at
a given position. The level of error seems , intuitively, suspiciously low.
Do you have data about the "actual" error as well as the perceived error?
 
Without at least some comparison of actual and perceived error I don't see how you could do anything useful.

A more detailed description what exactly you have as data would be useful.
 
Stephen Tashi said:
Do you have data about the "actual" error as well as the perceived error?

No, sorry, I was trying to estimate any possible error. I was wondering if there were ways to do this. I was wondering to what extent ( and if ) DK provided some means to do this. I have data about the perceived error and I was wondering if DK allowed to estimate the margin of under/evaluating or general mis-evaluation of error.
 
Not without a study how strong the effect is in your particular setup - and including such a study in your particular setup is probably the only reliable way to estimate that. I guess you cannot say anything about actual errors, just something about perceived errors.
 

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