Alpha Risk

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Alpha Risk

When testing a hypothesis, the risk of rejecting a piece of data that should have been accepted. Many tests reject some data as unusable or irrelevant. Alpha risk is the probability that the wrong data will be eliminated from the sample. It is also called type I error or alpha error. See also: Beta risk.
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They also advocated specifying the level for type I error rates to encourage auditors to avoid the pitfalls revealed in the research.
The first simulation study was conducted to verify that increased concurvity does result in increased standard error bias and, therefore, to inflated type I error. For each j in the set {0,0.1,0.2, ...
Type I errors involve rejecting material that is actually good while Type II errors occur when accepting material that is actually bad.