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Data & Analytics · Intermediate

Type I Error

Rejecting a true null hypothesis: a false positive, with probability α.

Definition

Examples include concluding a drug works when it doesn't, or flagging a good process as out of control. Multiple testing inflates the overall Type I error rate unless corrections such as Bonferroni are used.

Exam tip

Type I = false positive (α); Type II = false negative (β).

Related terms