What does a Type II error signify?

A Type II error, often referred to as a "false negative," occurs when a statistical test fails to reject the null hypothesis when it is, in fact, false. This means that the test concludes there is no difference or effect when there actually is one. In practical terms, this can lead to the incorrect assumption that a treatment or intervention does not work when it actually does. Understanding this concept is crucial for researchers and practitioners, as Type II errors can have significant implications in fields such as medicine, psychology, and social sciences, where recognizing and validating the existence of an effect or difference is essential for informed decision-making and effective practice.