Type II error

A Type II error occurs when a test fails to detect an effect or difference that actually exists. For example, imagine a medical test that is supposed to identify a disease. If the test results come back negative when the person actually has the disease, that's a Type II error. In this case, the error leads to a false sense of security, as the person may not receive necessary treatment. Essentially, it's the mistake of not recognizing something important that is true, which can have significant implications in various fields, including medicine, research, and decision-making.