The art of thinking · 2 · Perception and attention
Signal detection theory
Also known as: SDT, Detection theory
German: Signalentdeckungstheorie
Signal detection theory is a framework from psychophysics that describes decisions about whether a signal is present under uncertainty; it separates an observer’s sensitivity to the signal (d′) from the response criterion, and classifies outcomes as hits, misses, false alarms and correct rejections.
- Cognitive psychology
- Perception
- Human factors
- Decision making
In one sentence
Signal detection theory separates sensitivity from response bias in deciding whether a signal is present: hits, misses, false alarms, correct rejections.
Example
An inspector at a vision station flags faulty labels. A stricter criterion produces fewer false alarms but more misses, although the inspector’s sensitivity — the ability to tell good from faulty labels — stays the same.
What the research shows
Wilson P. Tanner Jr. and John A. Swets (1954) applied statistical decision theory to visual detection, and David M. Green and John A. Swets (1966) developed it for psychophysics. The theory assumes that both “noise only” and “signal plus noise” produce evidence that varies from trial to trial; the observer sets a criterion and responds “signal” when the evidence exceeds it. Two quantities follow: sensitivity (d′, the separation of the two distributions) and the response criterion or bias (c or β). Outcomes are hits, misses, false alarms and correct rejections; receiver operating characteristic (ROC) curves show how hits and false alarms change together as the criterion shifts. Harold Stanislaw and Natasha Todorov (1999) give the standard calculations.
Evidence status
Signal detection theory is a standard measurement framework in perception, memory, medical diagnosis, inspection and alarm research. Its common parametric measures rest on assumptions (for example equal-variance normal distributions) that often do not hold exactly; nonparametric and unequal-variance measures exist for that case. The theory describes decisions, it does not explain why the evidence is weak. In alarm research, Shlomo Breznitz described the “cry wolf” effect: frequent false alarms lower trust and response rates to later alarms.
How it applies
Every alarm and warning sets a trade-off between misses and false alarms. Signal detection theory explains why operators flooded with nuisance alarms shift their criterion — a background to alarm flooding and alarm management. The glossary “Applied cognitive psychology for information use” takes up warning habituation and hazard perception. Choosing alarm thresholds and priorities is an engineering and safety decision based on the risk assessment, not something the theory settles.
External references
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