What is a Type II error?

A Type II error occurs when a researcher fails to reject a null hypothesis that is actually false. This situation implies that the test did not identify a specified effect or difference when one truly exists. In practical terms, it means that the researcher concludes there is no significant effect or relationship when, in reality, there is one. This can lead to missed opportunities for further investigation or implications in various fields, such as medicine or social sciences, where detecting a true effect is crucial for progress and decision-making.

Understanding this concept is vital for researchers because it emphasizes the importance of the power of a statistical test, which is the probability of correctly rejecting a false null hypothesis. Thus, managing the risk of Type II errors is essential in designing experiments and interpreting research findings accurately.