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The two erroneous outcomes that the statistical process of hypothesis testing can produce (the decision to reject or failure to reject the null hypothesis). As shown in the table below, Type I error refers to rejecting the null hypothesis when it is true. The probability of a Type I error is represented by á (alpha) and is usually set at .05 by practicing researchers. A Type II error refers to the failure to reject the null hypothesis when it is false. The probability of a Type II error is symbolized by â (beta). Type I errors are known as “false positives” and Type II errors are known as “false negatives.”

Null TrueNull False
Decision madeReject NullType I errorCorrect
Accept NullCorrectType II error
10.4135/9781412972024.n2609
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