APFIVE In an experiment assessing the risk of a new drug’s side effects, the null hypothesis is not rejected at a 5% significance level (p-value = 0.08). What would happen if a Type II error occurred in this test?
TITLE: Error Types Overview: #000000
| Error Type | Definition |
|---|---|
| Type I Error | Incorrectly rejecting a true null hypothesis |
| Type II Error | Failing to reject a false null hypothesis |
The table above summarizes the definitions of Type I and Type II errors.
It would lead to rejecting the null hypothesis even though it is true, causing unnecessary alarm.
It would result in erroneously concluding that the drug has no significant side effects, when in fact it does, potentially compromising safety.
It would modify the confidence interval substantially, leading to a misinterpretation of the side effect rates.
It would increase the overall risk level in the study without affecting the conclusion of the hypothesis test.