Difference Between Power and Significance Level: Explained Simply

Power is the probability of rejecting the null hypothesis when, in fact, it is false.
Power is the probability of making a correct decision (to reject the null hypothesis) when the null hypothesis is false.
Power is the probability that a test of significance will pick up on an effect that is present.
Power is the probability that a test of significance will detect a deviation from the null hypothesis, should such a deviation exist.
Power is the probability of avoiding a Type II error.

The p-value is a number, calculated from a statistical test, that describes how likely you are to have found a particular set of observations if the null hypothesis were true.
P-values are used in hypothesis testing to help decide whether to reject the null hypothesis. The smaller the p-value, the more likely you are to reject the null hypothesis.

Significance (p-value) is the probability that we reject the null hypothesis while it is true. Power is the probability of rejecting the null hypothesis while it is false. Significance is thus the probability of Type I error, whereas 1−power is the probability of Type II error.

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