Minimum Detectable Effect Sets Sample Size
Explain how baseline rate, minimum detectable effect, power, and alpha determine whether an A/B test has enough sample.
MDE is where business value and sample size negotiate. Minimum detectable effect is the smallest change you care enough to detect. It links business judgment to statistics. A smaller MDE demands a larger sample because natural variation can easily hide or mimic tiny differences. A larger MDE needs less traffic, but it also means you are choosing not to reliably detect smaller wins. Sample-size planning also depends on baseline rate, alpha, and power. Alpha controls false positives; power controls the chance of detecting the chosen effect if it is real. Statistical significance at the end only has meaning if the…
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