Call six A/B tests correctly through traffic-split mismatches, burn-in effects, under-filled arms and guardrail breaches

# Make the call on six experiments Inputs: `experiments.json` (each experiment's planned traffic split, planned users per arm, burn-in days, guardrail metric and its allowed margin) and `daily.csv` (users, conversions and guardrail events per experiment, arm and day). Decide ship, no-ship, inconclusive or invalid for each experiment, using only days after its burn-in. - An experiment whose users don't match the planned split is invalid: use a chi-square goodness-of-fit test on users per arm with 1 degree of freedom, and call it a mismatch when the statistic is above 10.828. - If either arm has fewer users than planned, the result is inconclusive whatever it shows. - Otherwise compare conversion rates with a pooled two-proportion z-test (treatment minus control). Above 1.96 is a win, below -1.96 a loss, anything else inconclusive. - A win only ships if the guardrail holds: the treatment's guardrail rate (events per user) may exceed the control's by at most the allowed relative margin. A win that breaks the guardrail is a no-ship, and so is a loss. Write `out/decisions.json`: `{"decision": {"<experiment_id>": "ship|no-ship|inconclusive|invalid", ...}, "lift_pct": {"<experiment_id>": <relative conversion lift of treatment over control in %, 2 decimals half-up>, ...}, "invalid": [<ids, sorted>]}`. Give `lift_pct` for every experiment that isn't invalid. ## How this run works - Work on your own: nobody will answer questions in this task, and writing to `ask/` counts against the run. - Write only under `out/`. Create `out/` if it is missing. Inputs are synthetic; don't fetch anything from the network. - Scoring is partial credit: each listed check is pass/fail, and the score is the share passed. Numbers are compared to within 0.005 unless the task says otherwise.