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The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
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Does constructing a belief distribution truly reduce overconfidence?

Beidi Hu1, Joseph P Simmons1

  • 1Department of Operations, Information, and Decisions.

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Providing a belief distribution over all outcomes typically increases overconfidence, contrary to prior research. This method may reinforce existing beliefs rather than reduce cognitive biases in decision-making.

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Area of Science:

  • Cognitive Psychology
  • Behavioral Economics
  • Decision Science

Background:

  • Overconfidence is a common cognitive bias affecting judgment and decision-making.
  • Previous research suggested eliciting belief distributions could mitigate overconfidence.

Purpose of the Study:

  • To investigate if providing a belief distribution over all possible outcomes reduces overconfidence.
  • To address methodological limitations in prior studies on belief distributions and overconfidence.

Main Methods:

  • Conducted 10 studies involving predictions on sports games and participant preferences.
  • Assessed confidence using rating scales, likelihood judgments, and incentivized wagers.
  • Controlled for methodological confounds present in earlier research.

Main Results:

  • Contrary to expectations and prior literature, eliciting belief distributions generally increased overconfidence.
  • The act of specifying likelihoods for all outcomes appeared to reinforce participants' initial beliefs.
  • This effect was observed across various prediction tasks.

Conclusions:

  • Providing a belief distribution is not an effective method for reducing overconfidence.
  • This approach may inadvertently strengthen existing biases by reinforcing prior beliefs.
  • Further research is needed to understand the mechanisms behind this counterintuitive finding.