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Sensitivity and specificity
Statistical power
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Key terms:
error
false
hypothesis
false positives
neyman
type ii error
null hypothesis
false negatives
type i error
specificity
bayes
hypotheses
statistician
biometric
frr
kimball
nullified
spam filtering
two sources of error
neyman and pearson
wrong problem
statistical error
type i and type ii
alternative hypothesis
determine whether
null hypothesis when
information retrieval
cambridge university press
sensitivity and specificity
acceptable level
deciding whether
statistical hypothesis
sample size
reprinted at pp
various proposals for further extension
jerzy neyman
false positive rate
prior estimate
rate of false positives
egon pearson
error of failing to reject
tipo
rejecting the null hypothesis
error rate
error of rejecting
speculated hypothesis
false positives and false negatives
when the null hypothesis
joint statistical papers
significance level
Search external links cited by footnotes on Wikipedia page Type I and type II errors:
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