Question

In respect of type 1 error in the field of medical statistics, which one of the following is not correct?

• A. It is also called alpha error.
• B. It is often assigned a value of 0.05 in studies.
• C. It is equal to 1 minus the beta error.
• D. It is used to determine sample size.

Hint:

1 minus beta is the definition of power, not of alpha.

Answer 1

The Correct Option is C

Step 1: Define the two errors.
Alpha is the type 1 error, the risk of rejecting a null hypothesis that is actually true. Beta is the type 2 error, the risk of accepting a null hypothesis that is actually false.

Step 2: Define power separately.
Power of a study is 1 minus beta. This describes the chance of correctly detecting a real effect, and it has nothing to do with alpha directly.

Step 3: Test each statement.
Alpha error is indeed another name for type 1 error, so that statement holds. A 0.05 cut-off for alpha is standard practice, so that also holds. Alpha does feed into sample size calculations along with power and expected effect size, so that statement holds too. Only the claim that type 1 error equals 1 minus beta error is false, since that formula belongs to power, not to alpha.

Step 4: Conclude.
The wrong statement is that type 1 error is equal to 1 minus the beta error.