ab-test-significancelisted

# A/B Test Design & Significance Tell the user whether a test result is **real or noise**, and how big a test needs to be before it can answer the question. Most teams call tests too early on too little data; this keeps the decision honest with a proper two-proportion z-test. ## When to use The user has an A/B test result to evaluate, or wants to size a test before launching it. ## Workflow **To evaluate a result:** gather visitors and conversions for control and variant, pick a confidence level (usually 95%), and run the engine. **To plan a test:** take the baseline conversion rate and the minimum lift worth detecting (the MDE), and compute the required sample size. > Paths assume you installed with `npx skills add`. From a clone of this repo, use `skills/ab-test-significance/resources/…` instead. ```bash node .agents/skills/ab-test-significance/resources/significance.js # demo (5.0% vs 6.2%) node .agents/skills/ab-test-significance/resources/significance.js '{"control":{"visitors":4000,"conversions":200},"variant":{"visitors":4050,"conversions":250},"confidence":95}' node .agents/skills/ab-test-significance/resources/significance.js '{"plan":true,"baselineRate":5,"mde":1,"confidence":95,"power":80}' # sample size node .agents/skills/ab-test-significance/resources/significance.js --help ``` It returns rates, relative and absolute lift, z and p, a significance verdict at your confidence level, a confidence interval on the difference, or — in plan mode — the visitors