What we are going to do in this video is talk about the idea of power when we are dealing with significance tests. And power is an idea that you might encounter in a first-year statistics course. It turns out that it's fairly difficult to calculate, but it's interesting to know what it means and what are the levers that might increase the power or decrease the power in a significance test. So just to cut to the chase, power is a probability. You can view it as the probability that you're doing the right thing when the null hypothesis is not true. And the right thing is you should reject the null hypothesis if it's not true. So it's the probability of rejecting, rejecting your null hypothesis given that the null hypothesis is false.