Type I and type II errors
= Type I and type II errors
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For a null hypothesis $H_0$, a Type I error rejects $H_0$ when it is true, while a Type II error accepts $H_0$ when the alternative is true. If a test accepts $H_0$ on an event $A$, their conditional probabilities are $\alpha=P_0(A^c)$ and $\beta=P_1(A)$.
= Type I error
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= Type II error
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