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In null hypothesis testing, researchers make one of two formal decisions (to reject or retain the null hypothesis) concerning one of two possible states of reality (the null hypothesis is actually true or false). This intersection creates a matrix of four distinct possible outcomes. Two outcomes are correct decisions: rejecting a false null hypothesis and retaining a true one. The remaining two outcomes are statistical errors: rejecting a true null hypothesis (Type I error) and retaining a false null hypothesis (Type II error).

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