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 the power of your test is too high, very small and possibly uninteresting effects can become significant.

If you provide the comparison proportion and the size of your sample, Minitab will calculate the power of the test.

Suppose the firm is testing whether the proportion of people responding to their advertisement is different from the hypothesized proportion of 0.65 by at least 5% (comparison proportions of 0.6 and 0.7).

The results indicate that with 1000 observations and a hypothesized proportion of 0.65:

·    The test has a power of 0.906457 to detect a comparison proportion of 0.6. This means that if the population proportion is 0.60, there is a 90.6457% chance that the test will detect this difference.

·    The test has a power of 0.920779 to detect a comparison proportion of 0.7.