Type I and Type II Errors
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
- Type I error (rejecting a true null): False positive. Diagnosing a disease when it is not present, a false alarm. - Type II error (accepting a false null): False negative. Failing to diagnose a disease when it is present, a missed catch.
SCAFFOLDING EFFECT
Reduce cognitive load
- Risk preference setting: Before making a decision, clarify which type of error you would rather commit. For example, the judicial system prefers to "let a guilty person go free" (to prevent Type I errors), while nuclear power plant safety prefers a "false alarm" (to prevent Type II errors).
Anchor fast decisions
Type I error is "declaring an effect when there is none" (false positive), while Type II error is "declaring no effect when there is one" (false negative); they trade off against each other and must be weighed according to the costs.
MINIMUM ACTION
In progress 0/3Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Type_I_and_type_II_errorsverified
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