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Compatibility effects in the perception of dispersion
Christopher J Bechler1, Jonathan Levav2
1University of Notre Dame, United States.
Cognition
|June 1, 2022
Summary
People perceive less variability in data when average ratings match possible inputs, even if statistically unlikely. This compatibility principle influences judgments about data dispersion and its source.
Area of Science:
- Cognitive Psychology
- Decision Science
- Behavioral Economics
Background:
- Averages are commonly used to summarize data distributions.
- Understanding how people interpret averages is crucial for accurate data perception.
Purpose of the Study:
- To investigate how the compatibility of an average rating with possible inputs influences perceptions of distribution variance.
- To identify the psychological mechanisms underlying this effect.
Main Methods:
- Six experiments and four supplemental studies involving 16,988 participants.
- Comparison of perceived dispersion for compatible versus non-compatible average ratings on a discrete scale.
Main Results:
- Participants perceived less dispersion in distributions associated with compatible average ratings (e.g., 4.0) compared to non-compatible ones (e.g., 4.01).
- This effect persisted even when non-compatible averages were statistically more likely.
Conclusions:
- A compatibility principle explains this bias: higher input-output compatibility leads to greater perceived input frequency and lower perceived variance.
- This cognitive bias can impact decision-making and information search strategies.
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