When a test returns a result that is statistically nonsignificant, the question arises, “does this result mean there is no effect or did my study lack statistical power to detect?” It’s a fair question, but one which power analysis cannot answer.

Recall that statistical power is the probability that a test will correctly reject a false null hypothesis. Statistical power *only *has relevance when the null is false.

The problem is that a nonsignificant result does not tell us whether the null is true or false. To calculate power after the fact is to make an assumption (that the null *is* false) that is not supported by the data.