What is statistical power and what is a typical target level?

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Power is the probability that a study will detect a true effect if one exists. It reflects how likely the study is to uncover a real difference or association when there actually is one, and it equals 1 minus the probability of a Type II error (failing to detect an effect that is present). When planning a trial, researchers often target a power of 80% or 90%, meaning there’s an 80% or 90% chance of finding a true effect of the specified size given the chosen significance level and sample size. Achieving higher power makes it less likely that a real effect will be missed, but it typically requires a larger sample size, lower variability, or a larger true effect. This concept is distinct from controlling false positives (the Type I error rate) and from the actual sample size or trial duration, which are related planning aspects but different quantities. In practice, you set the desired power (commonly 0.8 or 0.9) when calculating the required sample size to balance resources with the ability to detect meaningful effects.