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Graded Assignment | Due Sunday 10.22.17 at 11:00 PM Attempts: Average: 15 7. An

ID: 3489242 • Letter: G

Question

Graded Assignment | Due Sunday 10.22.17 at 11:00 PM Attempts: Average: 15 7. An example of a hypothesis test and the required assumptions AaAa A graduate student is performing a study on a new antidepressant. The drug is supposed to reduce depression, but the graduate student realizes that it may do nothing or even increase depression, so nondirectional hypotheses and conduct a two-tailed test. She knows that the average score for all depressed people is 25, with a standard deviation of a-6. If she designates the mean for the population of depressed people who take the antidepressant as antidepressant, she can identify the null and alternative hypotheses as: she decides to formulate Ho: antidepressant-Ho The sample of 36 depressed people who tried out the new antidepressant scored an average of 23.3. Since the graduate student knows the standard deviation of the scores on the depression inventory for the population of people who are depressed, she intends to use a hypothesis test that uses the z-score of the sample mean as the test statistic (also known as the z test). First, she wants to make sure all the required assumptions are satisfied. Which of the following conditions is not a required assumption for the z test? O The standard deviation of the scores on the depression inventory is the same for those who take the antidepressant and those who don't. search

Explanation / Answer

1. The answer to the first question is “each member should be related in some way to the other.” Only only does this contradict the assumption below (participants should be randomly distributed) but it will also bias the results obtained from the study.

2. 0.674 (as showed in the label below).

3.

a. Z score is:

Z = (X - ) /
Z = (23.3 - 25) / 6
Z = -0.28333

b. The z score lies inside the critical region (because it is lesser than 0.674). This leads us to accept the null hypothesis because it shows that there is no significant difference between the scores of the population and scores of the participants.