The power of a test is the probability of correctly rejecting the null hypothesis when it is false. This is equivalent to one minus the probability of a Type II error (failing to reject the null when it is false).

• Option A is incorrect because the p-value measures the probability of observing the test statistic under the null hypothesis, which is related to Type I error (rejecting the null when it is true).
• Option B is incorrect because the probability of a Type I error is the significance level, not the power of the test.
• Option C is correct because the power of the test is directly linked to avoiding a Type II error.