Precision bias

Precision bias also known as numeracy bias is a form of cognitive bias^[1] in which an evaluator of information commits a logical fallacy as the result of confusing accuracy and precision.^[2] More particularly, in assessing the merits of an argument, a measurement, or a report, an observer or assessor falls prey to precision bias when they believe that greater precision implies greater accuracy (i.e., that simply because a statement is precise, it is also true); the observer or assessor are said to provide false precision.^[3]^[4]

The clustering illusion^[5] and the Texas sharpshooter fallacy^[6] may both be treated as relatives of precision bias. In these related fallacies, precision is mistakenly considered evidence of causation, when in fact the clustered information may actually be the result of randomness.

References

^ Proceedings of the 33rd Annual Meeting of the Cognitive Science Society (CogSci 2011), held in Boston, USA 20-32 July 2011 / L. Carlson, C. Hoelscher and T. Shipley (eds.): pp.1521-1526
^ "Practices of Science: Precision vs. Accuracy | manoa.hawaii.edu/ExploringOurFluidEarth". manoa.hawaii.edu. Retrieved 2022-10-22.
^ Lim, Daniel; DeSteno, David (2020). "Past adversity protects against the numeracy bias in compassion". Emotion. 20 (8): 1344–1356. doi:10.1037/emo0000655. ISSN 1931-1516. PMID 31414833. S2CID 198166331.
^ Jerez-Fernandez, Alexandra; Angulo, Ashley N.; Oppenheimer, Daniel M. (2014). "Show Me the Numbers: Precision as a Cue to Others' Confidence". Psychological Science. 25 (2): 633–635. doi:10.1177/0956797613504301. ISSN 0956-7976. PMID 24317423. S2CID 43824955.
^ Howard, Jonathan (2019), "Illusionary Correlation, False Causation, and Clustering Illusion", Cognitive Errors and Diagnostic Mistakes, Cham: Springer International Publishing, pp. 265–283, doi:10.1007/978-3-319-93224-8_15, ISBN 978-3-319-93223-1, S2CID 150016878, retrieved 2022-10-22
^ Thompson, W. C. (2009-09-01). "Painting the target around the matching profile: the Texas sharpshooter fallacy in forensic DNA interpretation". Law, Probability and Risk. 8 (3): 257–276. doi:10.1093/lpr/mgp013. ISSN 1470-8396.

External links

Truth Versus Precision In Economics, Thomas Mayer, Emeritus Professor of Economics, University of California
"Less Is More: Accuracy vs. Precision In Modeling", Susan Bachman et al. ("Many modelers assume that building with more precision yields a more accurate model.")

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[1] Proceedings of the 33rd Annual Meeting of the Cognitive Science Society (CogSci 2011), held in Boston, USA 20-32 July 2011 / L. Carlson, C. Hoelscher and T. Shipley (eds.): pp.1521-1526

[2] "Practices of Science: Precision vs. Accuracy | manoa.hawaii.edu/ExploringOurFluidEarth". manoa.hawaii.edu. Retrieved 2022-10-22.

[3] Lim, Daniel; DeSteno, David (2020). "Past adversity protects against the numeracy bias in compassion". Emotion. 20 (8): 1344–1356. doi:10.1037/emo0000655. ISSN 1931-1516. PMID 31414833. S2CID 198166331.

[4] Jerez-Fernandez, Alexandra; Angulo, Ashley N.; Oppenheimer, Daniel M. (2014). "Show Me the Numbers: Precision as a Cue to Others' Confidence". Psychological Science. 25 (2): 633–635. doi:10.1177/0956797613504301. ISSN 0956-7976. PMID 24317423. S2CID 43824955.

[5] Howard, Jonathan (2019), "Illusionary Correlation, False Causation, and Clustering Illusion", Cognitive Errors and Diagnostic Mistakes, Cham: Springer International Publishing, pp. 265–283, doi:10.1007/978-3-319-93224-8_15, ISBN 978-3-319-93223-1, S2CID 150016878, retrieved 2022-10-22

[6] Thompson, W. C. (2009-09-01). "Painting the target around the matching profile: the Texas sharpshooter fallacy in forensic DNA interpretation". Law, Probability and Risk. 8 (3): 257–276. doi:10.1093/lpr/mgp013. ISSN 1470-8396.

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v t e Biases
Cognitive biases	Acquiescence Ambiguity Affinity Anchoring Attentional Attribution Actor–observer Fundamental Group Ultimate Authority Automation Double standard Availability Mean world Belief Blind spot Choice-supportive Commitment Confirmation Selective perception Compassion fade Congruence Cultural Declinism Distinction Dunning–Kruger Egocentric Curse of knowledge Emotional Extrinsic incentives Fading affect Framing Frequency Frog pond effect Halo effect Hindsight Horn effect Hostile attribution Impact Implicit In-group Intentionality Illusion of transparency Mean world syndrome Mere-exposure effect Narrative Negativity Normalcy Omission Optimism Out-group homogeneity Outcome Overton window Precision Present Pro-innovation Proximity Response Restraint Self-serving Social comparison Social influence bias Spotlight Status quo Substitution Time-saving Trait ascription Turkey illusion von Restorff effect Zero-risk In animals
Statistical biases	Estimator Forecast Healthy user Information Psychological Lead time Length time Non-response Observer Omitted-variable Participation Recall Sampling Selection Self-selection Social desirability Spectrum Survivorship Systematic error Systemic Verification Wet
Other biases	Academic Basking in reflected glory Déformation professionnelle Funding FUTON Inductive Infrastructure Inherent In education Liking gap Media False balance Vietnam War South Asia United States Arab–Israeli conflict Ukraine Net Political bias Publication System justification Reporting White hat Ideological bias on Wikipedia
Bias reduction	Cognitive bias mitigation Debiasing Heuristics in judgment and decision-making
Lists: General Memory

See also

References

External links