A term often used in clinical research is statistical power. The power of a statistical test is the ability of the test to detect an effect, if the effect actually exists. In statistical terms, it is the probability that it will correctly lead to the rejection of a null hypothesis.

In some cases we may not be able to reject the null hypothesis, not because it is true, but because we do not have sufficient evidence against it. This might be because the experiment is not large enough to reject the null hypothesis. As such, the power of a test can be described as the probability of not making a Type II error (not rejecting the null hypothesis when in fact it is false).