Question

A team leader resonsible for the output of one assembly line that is supposed to be producing items that have a weight of 36 ounces wants to perform a hypothesis test to determine if the output is significantly different from that value. He knowd that the process is normally distributed with a population variance of 4 ounces. Once he completes the test, he discovers that his calculated z-value is negative. Given the information, which off the following best discribes what he should do?

Recognize that no error has been made and compare the absolute value of the computed z-value with that of the critical values in a z-table to see if it is significant or not.

Recognize that an error has been made because a compted z-value can never be negative. Because of this, he should repeat the experiment and see where the mistake was.

Recognize that an error has been made because a computed z-value should never be negative. Because of this, he should repeat the experiment and switch the data columns.

Recognize the no error has been made and, because the computed z-value is negative, conclude that the assembly line is "out of control" and search for the root cause of the problem.

Answer 1

Correct Choice : Recognize that no error has been made and compare the absolute value of the computed z-value with that of the critical values in a z-table to see if it is significant or not.

Explanation:

Clearly, in a hypothesis test with two-tailed case, there is possibility of obtaining a negative value of test-statistic and hence of z-score. So certainly, obtaining a negative z-score is not at all an error. Hence we rule out the second and third options. Now, for choosing between 1st and 4th options, merely obtaining a negative z-value doesn't mean that the process is out of control. We must verify whether the actual numerical value of z-score is crossing the critical z-value under the prescribed siginificance level. Therefore, 1st option is the right answer.

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