P-value under 5% but power under 80% Im trying to understand how to accurately report results on AB tests
If my type 1 error is 5% and type 2 is 20% , can we have instances where the p-value is < 0.05 and power is < 0.8?
If so, how ? What does it mean ?
Is something statistical significant when p-value is under 0.05 or power over 80% (assuming alpha and beta are defined to be 5% and 20%)?
EDIT: Im performing my power analysis during an experiment. Im trying to give updates on how a change in a button colour is performing. And in that update I want to specify the power it has.

Power depends on the $\alpha$-level, which you set, not on the p-value (which you calculate).
If you do a power calculation and determine that you have $80\%$ power to detect the difference of interest at the $\alpha$-level you've selected (often, but not necessarily, $\alpha = 0.05$), then that's the power. You don't even need to calculate a p-value for that to be the power. In fact, it might be common in certain fields not to have any data when the power calculation is performed, but to perform it in order to get funding for an experiment that will collect the data and result in subsequent calculations (such as p-values).
