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Published equation contexts

P(D∣H)P(D∣¬H)  >  P(¬H)P(H)⋅cfacmiss\frac{P(D \mid H)}{P(D \mid \lnot H)} \; > \; \frac{P(\lnot H)}{P(H)} \cdot \frac{c_{fa}}{c_{miss}}

Why this formula appears here

This is a rule about optimal thresholds, not merely an intuition, and it has a compact formal statement. A decision-maker observes ambiguous evidence D bearing on whether a state H holds — a predator is present, a partner is unfaithful, an approach signals romantic interest — against the alternative that it does not. Where cfac_{fa} is the fitness cost of a false alarm and cmissc_{miss} is the fitness cost of a miss, the threshold that minimizes total expected fitness cost is to infer H whenever: P(D∣H)P(D∣¬H)  >  P(¬H)P(H)⋅cfacmiss\frac{P(D \mid H)}{P(D \mid \lnot H)} \; > \; \frac{P(\lnot H)}{P(H)} \cdot \frac{c_{fa}}{c_{miss}}. When the two error costs are equal, the cost ratio on the right collapses to one, and the rule reduces to the ordinary Bayesian classifier that a norm blind to consequences would…

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PP

Symbol P

P is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

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DD

Symbol D

D is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

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HH

Symbol H

H is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

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cmissc_{miss}

Symbol c_miss

the fitness cost of a miss, the threshold that minimizes total expected fitness cost is to infer H whenever: [displayed formula].

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P(D∣¬H)P(D \mid \lnot H)

Denominator: P(D mid lnot H)

The complete quantity below the fraction bar; it must be nonzero for this division.

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How to interpret it

With a fixed numerator, increasing a nonzero denominator reduces the fraction.

Research cited beside this formula

Published contexts (1)

A symbol can carry a different meaning in another article. Each occurrence keeps its own guide and term definitions.

P(D∣H)P(D∣¬H)  >  P(¬H)P(H)⋅cfacmiss\frac{P(D \mid H)}{P(D \mid \lnot H)} \; > \; \frac{P(\lnot H)}{P(H)} \cdot \frac{c_{fa}}{c_{miss}}

Equation 6 · Evolutionary Psychology

Ecological Rationality: When Biases Are Adaptations

This equation states a bound: one expression must stay on the indicated side of the other under the article’s assumptions.

This is a rule about optimal thresholds, not merely an intuition, and it has a compact formal statement. A decision-maker observes ambiguous evidence D bearing on whether a state H holds — a predator is present, a partner is unfaithful, an approach signals romantic interest — against the alternative that it does not. Where cfac_{fa} is the fitness cost of a false alarm and cmissc_{miss} is the fitness cost of a miss, the threshold that minimizes total expected fitness cost is to infer H whenever: P(D∣H)P(D∣¬H)  >  P(¬H)P(H)⋅cfacmiss\frac{P(D \mid H)}{P(D \mid \lnot H)} \; > \; \frac{P(\lnot H)}{P(H)} \cdot \frac{c_{fa}}{c_{miss}}. When the two error costs are equal, the cost ratio on the right collapses to one, and the rule reduces to the ordinary Bayesian classifier that a norm blind to consequences would…

Meanings in this article

  • cfac_{fa}: the fitness cost of a false alarm.
  • cmissc_{miss}: the fitness cost of a miss, the threshold that minimizes total expected fitness cost is to infer H whenever: [displayed formula].
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