Answer:
<u>Type I error: </u>D. Reject the null hypothesis that the percentage of adults who retire at age 65 is less than or equal to 62 % when it is actually true.
<u>Type II error: </u>A. Fail to reject the null hypothesis that the percentage of adults who retire at age 65 is less than or equal to 62 % when it is actually false.
Step-by-step explanation:
A type I error happens when a true null hypothesis is rejected.
A type II error happens when a false null hypothesis is failed to be rejected.
In this case, where the alternative hypothesis is that "the percentage of adults who retire at age 65 is greater than 62%", the null hypothesis will state that this percentage is not significantly greater than 62%.
A type I error would happen when the conclusion is that the percentage is greater than 62%, when in fact it is not.
A type II error would happen when there is no enough evidence to claim that the percentage is greater than 62%, even when the percentage is in fact greater than 62% (but we still don't have evidence to prove it).
