Statistical Power & Sample Size Overview Power analysis plans the probability of rejecting a specified null under an assumed alternative. It answers how many independent experimental units are needed to detect a scientifically important effect , or what effects a feasible sample could detect. Choose the inferential goal first: precision, equivalence, noninferiority, or sequential monitoring need their own calculations; the bundled superiority-test helpers do not cover them. Four quantities are locked together for any given test: sample size (n) , effect size , significance level (α) , and pow…