Question:
In respect of type 1 error in the field of medical statistics, which one of the following is not correct?
In respect of type 1 error in the field of medical statistics, which one of the following is not correct?
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1 minus beta is the definition of power, not of alpha.
Updated On: Jul 7, 2026
- It is also called alpha error.
- It is often assigned a value of 0.05 in studies.
- It is equal to 1 minus the beta error.
- It is used to determine sample size.
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The Correct Option is C
Solution and Explanation
Step 1: Understanding the Question.
Note: the source answer key marks a different option, but that marked option is a true statement, so based on the standard definitions in biostatistics, the answer worked out below is the one that is actually incorrect.
Step 2: Key Formula or Approach.
Type 1 error, written as alpha, is the chance of wrongly rejecting a true null hypothesis. Type 2 error, written as beta, is the chance of wrongly failing to reject a false null hypothesis. Power of a study is defined as 1 minus beta, not as anything involving alpha.
Step 3: Detailed Explanation.
Checking each option: calling type 1 error the alpha error is correct terminology. Setting alpha at 0.05 is indeed the conventional threshold used in most studies, so that statement is also correct. Saying type 1 error is used, together with the expected effect size and beta, to determine the sample size needed for a study is also correct, since alpha is one of the inputs to every sample size formula. The statement that type 1 error equals 1 minus beta error is wrong, because 1 minus beta is the definition of statistical power, a completely different quantity from alpha.
Step 4: Final Answer.
The incorrect statement is that type 1 error is equal to 1 minus the beta error.
Note: the source answer key marks a different option, but that marked option is a true statement, so based on the standard definitions in biostatistics, the answer worked out below is the one that is actually incorrect.
Step 2: Key Formula or Approach.
Type 1 error, written as alpha, is the chance of wrongly rejecting a true null hypothesis. Type 2 error, written as beta, is the chance of wrongly failing to reject a false null hypothesis. Power of a study is defined as 1 minus beta, not as anything involving alpha.
Step 3: Detailed Explanation.
Checking each option: calling type 1 error the alpha error is correct terminology. Setting alpha at 0.05 is indeed the conventional threshold used in most studies, so that statement is also correct. Saying type 1 error is used, together with the expected effect size and beta, to determine the sample size needed for a study is also correct, since alpha is one of the inputs to every sample size formula. The statement that type 1 error equals 1 minus beta error is wrong, because 1 minus beta is the definition of statistical power, a completely different quantity from alpha.
Step 4: Final Answer.
The incorrect statement is that type 1 error is equal to 1 minus the beta error.
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