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Precision bias information


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.

  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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Precision bias

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Precision bias also known as numeracy bias is a form of cognitive bias in which an evaluator of information commits a logical fallacy as the result of...

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Accuracy and precision

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plays a central role, prefers to use the terms bias and variability instead of accuracy and precision: bias is the amount of inaccuracy and variability is...

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False precision

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leads to overconfidence in the accuracy, named precision bias. Madsen Pirie defines the term "false precision" in a more general way: when exact numbers are...

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Exponent bias

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interpreting the floating-point number, the bias is subtracted to retrieve the actual exponent. For a half-precision number, the exponent is stored in the range...

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Precision and recall

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(DeltaP). Accuracy is a weighted arithmetic mean of Precision and Inverse Precision (weighted by Bias) as well as a weighted arithmetic mean of Recall and...

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Funnel plot

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treatment effect against a measure of study precision. It is used primarily as a visual aid for detecting bias or systematic heterogeneity. A symmetric inverted...

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Bias

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may allow speedier choices when speed is more valuable than precision. Other cognitive biases are a "by-product" of human processing limitations, coming...

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Sampling bias

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In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher...

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Extended precision

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Extended precision refers to floating-point number formats that provide greater precision than the basic floating-point formats. Extended precision formats...

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Bias of an estimator

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In statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter...

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Minifloat

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half-precision has 5 exponent bits with bias 15 ( 2 5 − 1 − 1 = 15 {\displaystyle 2^{5-1}-1=15} ), IEEE single-precision has 8 exponent bits with bias 127...

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Anchoring effect

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experiments that attempt to mitigate the decision heuristic of anchoring bias is either marginally significant or not successful at all, it can be found...

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Personalized medicine

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machine learning-based tools for precision medicine. Precision medicine may be susceptible to subtle forms of algorithmic bias. For example, the presence of...

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Rounding

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between the domain and range. With finite precision (or a discrete domain), this translates to removing bias. A rounding method should have utility in...

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Length time bias

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Length time bias (or length bias) is an overestimation of survival duration due to the relative excess of cases detected that are asymptomatically slowly...

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IEEE 754

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represented exactly. Further, the exponent is not represented directly, but a bias is added so that the smallest representable exponent is represented as 1...

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