Analyze An A/B Test Dataset

Data challenge: analyze an A/B test dataset and report findings (take-home style; candidates are told ChatGPT use is allowed for analysis). Asked in the data challenge stage. OP answered "Ab testing" when asked what kind of data challenge it was; another commenter notes ChatGPT is allowed.

Using the supplied dataset and any accompanying data dictionary:

1. State the hypothesis, identify the unit of randomization and unit of analysis, and define a primary metric plus relevant guardrails.
2. Check data quality, including sample ratio mismatch, missingness, duplicates, exposure validity, and pre-treatment balance.
3. Estimate treatment effects with confidence intervals and appropriate statistical tests. Explain any transformation, clustering, or segmentation choices.
4. Assess practical significance against an explicit MDE, discuss possible peeking or multiple-comparison issues, and report limitations.
5. Provide a concise ship, do not ship, or investigate recommendation supported by reproducible analysis.

Submit your analysis, code, assumptions, and a brief written findings report. Do not treat statistical significance alone as sufficient evidence to ship.