So "type error" is a false positive, "type I error" is a false negative, and "type II error" is when a variable has the wrong type, right?
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@ModelOfEnsemble@DeityOfReligion How am I going to get that below 5%?Thanks. Twitter will use this to make your timeline better. UndoUndo
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@ModelOfEnsemble@DeityOfReligion@MemberOfSpecies Type i error is when you think you had a type 1 error but actually you didn't. -
@MaskOfFace@ModelOfEnsemble@DeityOfReligion@MemberOfSpecies empirical type error: the observed frequency differs from the probability
End of conversation
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