A Type II error refers to which situation?

A Type II error occurs when a researcher fails to reject a false null hypothesis, meaning they do not find a significant result even though there is actually one present. This situation reflects a missed opportunity to detect an effect or a relationship that genuinely exists in the data. This type of error is particularly concerning because it can lead to the misconception that a treatment or intervention is ineffective when, in truth, it may be beneficial.

In the context of hypothesis testing, a Type II error typically involves a situation where the statistical power of the test is insufficient to detect the effect, which can arise from various factors such as a small sample size, low effect size, or high variability in the data. Understanding this concept is crucial for researchers when designing studies, as they must consider how to minimize the risk of Type II errors to ensure robust and reliable findings.