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Noise Increases Anchoring Effects.

Chang-Yuan Lee1, Carey K Morewedge1

  • 1Department of Marketing, Questrom School of Business, Boston University.

Psychological Science
|December 8, 2021
PubMed
Summary

Anchoring effects increase with stimulus magnitude because greater noise amplifies anchoring bias. This study reveals how stimulus magnitude predicts the size and replicability of anchoring effects in judgment.

Keywords:
anchoring biasjudgment under uncertaintynoisenumerical cognitionopen dataopen materialspreregistered

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Area of Science:

  • Cognitive Psychology
  • Decision Science
  • Behavioral Economics

Background:

  • Anchoring effects are common judgment biases, but the interplay between bias and noise remains unclear.
  • Existing theories do not fully explain how judgmental noise modulates anchoring effects.
  • Understanding this relationship is crucial for predicting judgment accuracy and bias.

Purpose of the Study:

  • To introduce and test a theoretical framework distinguishing anchoring effects, anchoring bias, and judgmental noise.
  • To investigate how stimulus magnitude influences the size and replicability of anchoring effects.
  • To elucidate the role of psychophysical noise in amplifying anchoring bias.

Main Methods:

  • Developed a theoretical framework differentiating anchoring effects, bias, and noise.
  • Conducted 11 preregistered experiments (N = 3,552) manipulating stimulus magnitudes.
  • Compared effects of relevant and irrelevant anchors across various familiar and novel stimuli.

Main Results:

  • Anchoring effects significantly increased with stimulus magnitude for both familiar and novel stimuli.
  • Psychophysical noise, driven by scalar variability, widened the perceived range of stimulus values.
  • Noise amplified anchoring bias, but noise alone did not produce anchoring effects.

Conclusions:

  • Stimulus magnitude is a key predictor of anchoring effect size and replicability.
  • Psychophysical noise modulates anchoring effects by amplifying anchoring bias.
  • The findings provide a novel method for studying bias-noise interactions in judgment under uncertainty.