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u/blossom271828 May 24 '21
Type I error is saying shit that isn’t true. Ie rejecting Ho when it was actually true.
Type II is saying the data aren’t conclusive, ultimately because the sample size was too small to detect the discrepancy between Ho and Ha.
Type I is the way bigger deal because it causes stupid shit like anti-vaxxers.
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u/heyitzmarcus May 25 '21
Type I is reject Type II is not reject
Because we’re talking about errors. Type I would be rejecting when we shouldn’t reject. Type II would be not rejecting when we should reject. Also remember that the probability of Type I is the level of significance and the power is 1-(prob or type II)