Power is the probability of correctly rejecting a false null hypothesis. Power is therefore defined as: 1 - b where b is the Type II error probability. If the power of an experiment is low, then there is a good chance that the experiment will be inconclusive. That is why it is so important to consider power in the design of experiments. There are methods for estimating the power of an experiment before the experiment is conducted. If the power is too low, then the experiment can be redesigned by changing one of the factors that determine power.

Consider a hypothetical experiment designed to test whether rats brought up in an enriched environment can learn mazes faster than rats brought up in the typical laboratory environment (the control condition). Two groups of 12 rats each are tested. although the experimenter does not know it, the population mean number of trials it takes to learn the maze is 20 for the enriched condition and 32 for the control condition. The null hypothesis that the enriched environment makes no difference is therefore false.