Final answer:
A Type I error happens when the null hypothesis is incorrectly rejected, while a Type II error occurs when a false null hypothesis is wrongly not rejected. The question asks about a Type I error, which is the rejection of a true null hypothesis. The correct answer is B. reject the null hypothesis when it is actually true.
Step-by-step explanation:
A Type I error occurs when we reject the null hypothesis when it is actually true. This is a false positive, where we incorrectly conclude that there is an effect or a difference when none exists. For example, it would be a Type I error if we reject the null hypothesis that the percentage of adults who have jobs is at least 88 percent when that percentage is actually at or above 88 percent.
Conversely, a Type II error occurs when we do not reject the null hypothesis when it is actually false. This is a false negative, where we fail to detect an effect or a difference that is present.
For example, it would be a Type II error if there is not enough evidence to conclude that the proportion of first-time brides who are younger than their grooms differs from 50 percent when, in fact, the proportion does differ from 50 percent.
A Type I error occurs when we reject the null hypothesis when it is actually true (option B). This means that we mistakenly conclude that there is a significant effect or difference when there is not enough evidence to support that conclusion.