The power of a test is its ability to detect an effect. It is always possible that, due to sampling error, a test will lead you to the wrong conclusion. Assessing power allows you to determine the probability that the test will correctly identify an effect if one exists.

If a test has low power, you may fail to detect an effect and mistakenly conclude that none exists.

If you provide the comparison rate that you want to be able to detect and the size of each sample, Minitab will calculate the power of the test.

For the post office data, the analyst wants to know what power she will get if she collects data over 30, 40, or 50 days and wants to detect a comparison rate of 240 or 260. The results indicate:

·    with a sample size of 30, the test has a power of 0.696516 when the comparison rate is 240 and a power of 0.679181 when the comparison rate is 260.

·    with a sample size of 40, the test has a power of 0.815189 when the comparison rate is 240 and a power of 0.799714 when the comparison rate is 260.

·    with a sample size of 50, the test has a power of 0.891477 when the comparison rate is 240 and a power of 0.879232 when the comparison rate is 260.