Final answer:
A Type II error occurs when the null hypothesis is not rejected, even though it is actually false. This can happen when the sample size is too small or when the effect size is too small to be detected with the given data.
Step-by-step explanation:
A Type II error occurs when the null hypothesis is not rejected, even though it is actually false. In other words, it is the error of not detecting a difference or effect that truly exists. This can happen when the sample size is too small or when the effect size is too small to be detected with the given data. An example of a Type II error would be failing to reject the null hypothesis that a new drug has no effect, when it actually does have an effect.