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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Replying to @MemberOfSpecies
@MemberOfSpecies "type 0" error is when not even wrong enough to be considered an error.2 replies 0 retweets 1 like -
Replying to @DeityOfReligion
@DeityOfReligion@MemberOfSpecies "type III error" is when you forget which meaningless number maps to which concept2 replies 2 retweets 8 likes
Replying to @ModelOfEnsemble
@ModelOfEnsemble @DeityOfReligion How am I going to get that below 5%?
11:39 PM - 9 Dec 2014
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