Power (statistical)
The probability that a statistical test will correctly reject a false null hypothesis, effectively measuring the test's ability to detect a true effect.
Think of It Like This
Like a metal detector's sensitivity; higher power means you are much less likely to accidentally walk right over a buried gold coin.
Statistical power is heavily influenced by the sample size, the significance level (alpha), and the true effect size. A low-power experiment (often due to insufficient data) risks committing a Type II error, meaning it fails to recognize an algorithm improvement that genuinely exists. It is crucial for planning A/B tests.