Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significan…
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name: ab-test-analysis
description: "Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant."
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## A/B Test Analysis
Evaluate A/B test results with statistical rigor and translate findings into clear product decisions.
### Context
You are analyzing A/B test results for **$ARGUMENTS**.
If the user provides data files (CSV, Excel, or analytics exports), read and analyze them directly. Generate Python scripts for statistical calculations when needed.
### Instructions
1. **Understand the experiment**:
- What was the hypothesis?
- What was changed (the variant)?
- What is the primary metric? Any guardrail metrics?
- How long did the test run?
- What is the traffic split?
2. **Validate the test setup**:… load the full skill through Skill Me