A Bayesian perspective on Likert scales and central tendency.

Area of Science:

• Cognitive Psychology
• Decision Science
• Behavioral Economics

Background:

• Central tendency bias is a common finding in Likert scale responses.
• Existing explanations lack a unified theoretical framework.

Purpose of the Study:

• To offer a Bayesian perspective on central tendency bias.
• To explain the bias as a natural consequence of probability estimation on Likert scales.

Main Methods:

• Theoretical modeling using Bayesian inference.
• Two empirical studies employing Likert scale experiments.

Main Results:

• The Bayesian model successfully predicts the observed central tendency bias.
• Empirical data aligns with the theoretical predictions of probability estimation.

Conclusions:

• Central tendency bias can be understood as an optimal Bayesian strategy for response generation.
• This perspective provides a parsimonious explanation for a robust experimental finding.