What is a Type II error?

A Type II error occurs when a hypothesis test fails to reject the null hypothesis even though it is false, indicating that the test did not detect a true effect or difference that actually exists in the population. This means that the research may conclude there is no significant difference or effect when, in reality, one is present. In other words, a Type II error represents a situation where the statistical test lacks sufficient power to identify a genuine difference.

This distinction is crucial for understanding the implications of study results. It highlights the need for careful consideration of sample size, effect sizes, and the power of the statistical tests used in research to minimize the risk of Type II errors, thereby enhancing the reliability of the conclusions drawn from the study.