American Board of Surgery Qualifying Exam (ABS QE) Practice Test

What is a Type II error related to in hypothesis testing?

1. Rejecting a true null hypothesis

2. Accepting a false null hypothesis

3. Finding a difference when none exists

4. Correctly identifying a true null hypothesis

The correct answer is: Accepting a false null hypothesis

A Type II error, commonly denoted as beta (β), occurs when a false null hypothesis is accepted. In hypothesis testing, the null hypothesis typically states that there is no effect or difference between groups. When a Type II error happens, it means that despite evidence suggesting that a treatment or intervention was effective (or that a difference exists), the statistical test fails to reject the null hypothesis. This concept is crucial in clinical studies, as it highlights the risk of missing meaningful effects or differences when they are present, leading to potentially incorrect conclusions regarding the efficacy of an intervention. The focus on the acceptance of a false null hypothesis is essential for understanding the limitations of statistical tests in practice. Researchers must be aware of this error because it can result in the dismissal of potentially beneficial treatments or findings, which could have significant implications for patient care and scientific advancement. In contrast, the other answer choices involve scenarios related to incorrect decisions in hypothesis testing but describe different types of errors or correct conclusions, which do not capture the essence of what constitutes a Type II error.