BiasReasoning & flexibility · Cognitive Bias · Entry 127
Value Selection Bias – choosing supplied numbers instead of constructing the Bayesian answer
Value Selection Bias is a narrow reasoning pattern studied in Bayesian diagnostic problems. When participants did not derive the correct solution, their incorrect answers were strongly drawn toward numerical values already supplied in the problem. The effect concerns problem representation, reference classes, and solution construction; it is not evidence that people generally rely on old prices, stale KPIs, or outdated travel estimates.
Where it can show up
- Diagnostic probabilities – a number printed in the problem is selected because it looks answer-like even though the requested quantity requires a different reference class.
- Bayesian reasoning – the solver recognizes relevant values but does not organize them into the relationship needed for the target probability.
- Explanation – a calculation error is blamed even when the actual mistake was selecting the wrong supplied values before calculation began.
A practical countermeasure
- State the target quantity and reference class before selecting numbers.
- Write the required relationship or calculation explicitly.
- Check that every selected value belongs to the same reference frame as the question.
- If you use a supplied number directly, explain why no transformation or calculation is required.
Evidence review
supported in Bayesian reasoning tasks; limited independent replicationWhat the evidence supports
Value Selection Bias is a narrow reasoning pattern reported in Bayesian diagnostic problems: when participants did not derive the correct solution, incorrect answers were strongly drawn toward numerical values already present in the problem. The evidence supports this behavior across multiple problem variations in the authors' research program, but it should not be generalized to any situation where a person uses an old price, stale KPI, or convenient number.
How researchers describe the pattern
The research links value selection to reference dependence and problem representation. When reasoners are uncertain about how to construct the needed calculation, salient values supplied by the problem can look like candidate answers. Numerical ability and the way the reference class is represented affect accuracy, so the pattern is more specific than a generic preference for available numbers.
Practical interpretation
In a probability or diagnostic problem, state the target quantity and reference class before looking for a number to copy into the answer. Write the required relationship or calculation explicitly, then check whether the selected values actually belong to that relationship. If no calculation is needed, be able to explain why rather than assuming that a supplied number must be the answer.
Reviewed sources
- Reference Dependence in Bayesian Reasoning doctoral dissertation / multi-experiment research program · 2019
- Reference Dependence in Bayesian Reasoning: Value Selection Bias, Congruence Effects, and Response Prompt Sensitivity peer-reviewed experiments · 2022 · DOI 10.3389/fpsyg.2022.729285
Editorial review: 2026-08-18. Evidence status describes this entry, not every study ever published on the topic.