Type I & Type II errors
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Rate of type I error
Called the "size" of the test and denoted by the Greek letter α (alpha). It usually equals the significance level of a test.
Rate of the type II error
Denoted by the Greek letter β (beta) and related to the power of a test (which equals 1−β)
Type II error
False negative: fail to reject/ accept the null hypothesis when the null hypothesis is false
Type I error
False positive: rejecting the null hypothesis when the null hypothesis is true