Statistical Power

Statistical power refers to a test’s ability to detect a difference or effect when it truly exists. In other words, it is related to avoiding a Type II error. Power depends on factors such as sample size, effect size, noise level, and the chosen significance threshold. Low-powered tests may fail to identify meaningful effects and create a false sense of certainty. Power analysis is critical in experiment design, A/B testing, and model comparison because a poorly designed test may answer an important question with misleading silence.