What is a Type II error?

A Type II error occurs when a researcher fails to reject the null hypothesis when it is actually false. This means that a significant effect or difference exists in reality, but the statistical test does not detect it, leading to the conclusion that there is no effect. In other words, the test misses an important finding or relationship that should have been identified. Recognizing this error is crucial in research, as it can lead to ineffective conclusions and missed opportunities to further explore or act upon real phenomena.

Understanding Type II errors is essential for refining study designs and ensuring that tests are adequately powered to detect true effects, ultimately contributing to more accurate and reliable research outcomes.