To calculate the Probability of a Type I Error (\(P(\text{Type I Error})\)):
\[ P(\text{Type I Error}) = \alpha \]
Where:
A Type I Error, also known as a “false positive,” occurs when a statistical hypothesis test incorrectly rejects a true null hypothesis. This means that the test indicates that there is an effect or a difference when in fact there is none. The significance level (\(\alpha\)) is the probability of making a Type I Error, and it is set by the researcher before conducting the test.
Let's assume the following value:
Using the formula:
\[ P(\text{Type I Error}) = 0.05 \]
The Probability of a Type I Error is 0.05 or 5%.
Let's assume the following value:
Using the formula:
\[ P(\text{Type I Error}) = 0.01 \]
The Probability of a Type I Error is 0.01 or 1%.
