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Type I error refers to one of two kinds of error of inference that could be made during statistical hypothesis testing. The concept was introduced by J. Newman and E. Pearson in 1928 and formalized in 1933. A Type I error occurs when the null hypothesis (Ho), that there is no effect or association, is rejected when it is actually true. A Type I error is often referred to as a false positive, which means that the hypothesis test showed an effect or association, when in fact there was none.

In contrast, a Type II error occurs when the null hypothesis fails to be rejected when it is actually false. The relation between the Type I error and Type II error is summarized in Table 1.

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