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The diversity effect in inductive reasoning depends on sampling assumptions.

Brett K Hayes1, Danielle J Navarro2, Rachel G Stephens2

  • 1School of Psychology, University of New South Wales, Sydney, NSW, 2052, Australia. b.hayes@unsw.edu.au.

Psychonomic Bulletin & Review
|January 27, 2019
PubMed
Summary
This summary is machine-generated.

The diversity effect in inductive reasoning is stronger when evidence is perceived as intentionally selected (strong sampling). This effect is reduced when evidence is believed to be randomly chosen (weak sampling).

Keywords:
Bayesian modelingCategory-based inductionEvidence diversityRelevance theorySampling assumptions

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Area of Science:

  • Cognitive Psychology
  • Decision Science
  • Philosophy of Science

Background:

  • The diversity effect describes how novel properties are generalized more readily from diverse evidence samples than similar ones.
  • This phenomenon is crucial for understanding inductive reasoning and generalization.
  • Previous research has not fully explored the role of sampling assumptions in the diversity effect.

Purpose of the Study:

  • To investigate the influence of sampling assumptions on the diversity effect in inductive reasoning.
  • To test whether the diversity effect is moderated by beliefs about evidence selection (strong vs. weak sampling).
  • To develop and validate a Bayesian model explaining the observed effects.

Main Methods:

  • A Bayesian model was developed to predict generalization based on sampling assumptions.
  • An experimental study presented inductive arguments with diverse or nondiverse evidence under strong and weak sampling conditions.
  • Participants' generalization patterns were analyzed under different sampling conditions.

Main Results:

  • A robust diversity effect was observed under strong sampling conditions.
  • The diversity effect was significantly attenuated under weak sampling conditions.
  • The Bayesian model accurately predicted that nondiverse evidence is most affected by sampling assumptions, showing more restricted generalization under strong sampling.

Conclusions:

  • Beliefs about how evidence is generated critically influence which evidence characteristics are considered relevant for inductive reasoning.
  • The diversity effect is not solely a property of the evidence but is modulated by the perceived intentionality of its selection.
  • Understanding sampling assumptions is key to explaining variations in inductive generalization.