> For the complete documentation index, see [llms.txt](https://developer.harness.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developer.harness.io/feature-management-experimentation/use-fme/experimentation/setup/power-analysis.md).

# Power analysis

Power measures an experiment's ability to detect an effect, if possible. Formally, the power of an experiment is the probability of rejecting a false null hypothesis.

A commonly used value for statistical power is 80%, which means that the metric has 80% chance of reaching significance if the true impact is equal to the minimum likely detectable effect. Assuming all else is equal, a higher power increases the recommended sample size needed for your feature flag. In statistical terms, the power threshold is equivalent to 1 - β.

For more information, see the [Power threshold](/feature-management-experimentation/use-fme/experimentation/setup/experiment-settings.md#power-threshold) documentation.