What is a type II error?

What is a type II error?

• A. Rejecting a true null hypothesis
• B. Failing to reject a false null hypothesis
• C. Accepting a confirmed result
• D. Incorrectly accepting the null hypothesis

Answer: (B)

A type II error occurs when a researcher fails to reject a null hypothesis that is actually false. In simpler terms, this means that despite evidence suggesting an effect or a difference, the researcher concludes that there isn't one and maintains the assumption that the null hypothesis is true. This is problematic because it can lead to missed opportunities to identify important relationships or effects that are truly present. In statistical terms, it represents a situation where the sensitivity of the test is insufficient to detect an actual effect, thus resulting in a false-negative conclusion. Understanding type II errors is critical in hypothesis testing for determining the power of a statistical test, which reflects its ability to detect a true positive when one exists.

A type II error occurs when a researcher fails to reject a null hypothesis that is actually false. In simpler terms, this means that despite evidence suggesting an effect or a difference, the researcher concludes that there isn't one and maintains the assumption that the null hypothesis is true. This is problematic because it can lead to missed opportunities to identify important relationships or effects that are truly present.

In statistical terms, it represents a situation where the sensitivity of the test is insufficient to detect an actual effect, thus resulting in a false-negative conclusion. Understanding type II errors is critical in hypothesis testing for determining the power of a statistical test, which reflects its ability to detect a true positive when one exists.