ab-test-setup

提供严格的 A/B 测试设定流程、假设与执行准备检查清单。

把 A/B 测试从假设到上线的每一步都规范化，帮你把问题背景、假设、核心指标、样本量（统计功效）和执行就绪度都梳理清楚，防止中途偷窥（peeking）或设计缺陷。适合需要做可靠且可解释的在线实验，而不是临时跑个报表。特别之处在于内置强制关卡，能有效避免常见实验陷阱。

# A/B Test Setup

## 1️⃣ Purpose & Scope

Ensure every A/B test is **valid, rigorous, and safe** before a single line of code is written.

- Prevents "peeking"
- Enforces statistical power
- Blocks invalid hypotheses

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## 2️⃣ Pre-Requisites

You must have:

- A clear user problem
- Access to an analytics source
- Roughly estimated traffic volume

### Hypothesis Quality Checklist

A valid hypothesis includes:

- Observation or evidence
- Single, specific change
- Directional expectation
- Defined audience
- Measurable success criteria

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## 3️⃣ Hypothesis Lock (Hard Gate)

Before designing variants or metrics, you MUST:

- Present the **final hypothesis**
- Specify:
  - Target audience