ab-test-analysis

仓库创建 2026年3月2日最近提交 23 天前SkillHot 收录 20 天前

▸ 精选理由

把统计结论转成明确产品决策，能处理导出文件并生成可复现的 Python 脚本。

这个 Skill 做什么

对 A/B 测试结果做显著性检验、样本检验并给出上线/延长/停止建议。

帮你把 A/B 实验的结果用统计学方法“量化”——做显著性检验、样本量校验和置信区间，最后给出上线/延长/停止的建议。常用在判定某个 variant 是否真的比 baseline 好的时候。还能直接读入 CSV/Excel 数据并生成 Python 脚本复现计算，方便审计和复查。

▸ 展开 SKILL.md 英文原文

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.

数据与抓取A/B测试统计分析决策建议通用

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SKILL.MD 节选查看完整文件 ↗

## 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**:
   - **Sample size**: Is the sample large enough for the expected e

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