What is the consequence of a Type II error?

A Type II error occurs when a researcher fails to reject a null hypothesis that is actually false. This means that the outcome leads to a conclusion that there is no effect or difference when, in reality, one exists. In practical terms, the consequence is that the researcher might overlook an important finding or fail to identify a significant relationship, which could impact decision-making or further research. In experiments or studies, this error highlights the potential downsides of having insufficient power in statistical tests or the need for improved methods to detect true effects.

The understanding of Type II error is crucial in hypothesis testing, where the goal is to make informed decisions based on the data available. When a false null hypothesis is not rejected, it can lead to missed opportunities to innovate or correct issues that might be present, thus affecting the overall effectiveness of the research process.