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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Type 1 errors are a false positive: a researcher states that a specific relationship exists when in fact it does not.
In this case, an overestimation of a given climate impact is analogous to type 1 errors (i.
2013), effectively favoring the risk of type 2 errors to lower the chances of type 1 errors.
We highlight this example as an instance of how type 1 errors could potentially manifest in scientific assessments.
We suggest that assessment can further institutionalize the aversion to type 1 errors and attendant risk of committing type 2 errors.
2012) and thus provides an example of a possible type 1 error.
Naturally, varying situations and contexts apply different decision rules in considering type 1 versus type 2 errors, and type 1 error aversion is beneficial in certain circumstances.
Right now, credit unions may be making too many Type 1 errors in their loan programs," Rick said.
In lending, correspondingly, a Type 1 error would be rejecting a good loan, while a Type 2 error would be writing a bad loan, the economist said.
Every attempt should be made to keep type 1 errors to a minimum.
Pre decided numbers will not prevent the type 1 error but will limit the number of comparisons.
Here, only type 1 errors are usually applied, but type 2 errors should also be taken into consideration.