Final answer:
In the context of the problem, Type 1 error refers to the rejection of the null hypothesis when it is actually true. Type 2 error refers to the failure to reject the null hypothesis when it is actually false. Power refers to the probability of correctly rejecting the null hypothesis when it is false.
Step-by-step explanation:
In the context of the problem, Type 1 error refers to the rejection of the null hypothesis when it is actually true. In this case, it would mean concluding that people with withdrawal symptoms overestimate the elapsed time, when in fact they do not.
Type 2 error, on the other hand, refers to the failure to reject the null hypothesis when it is actually false. In this case, it would mean concluding that people with withdrawal symptoms do not overestimate the elapsed time, when in fact they do.
Power, in the context of this problem, refers to the probability of correctly rejecting the null hypothesis when it is false. It is the complement of the Type 2 error rate.
A high power indicates a higher likelihood of detecting a true effect. In this study, a high power would indicate a higher likelihood of correctly concluding that people with withdrawal symptoms overestimate the elapsed time.