ab-testing
Design and analyze A/B tests and controlled experiments for data-driven decisions. Use for: experiment design, hypothesis formulation, sample size calculation, statistical significance testing, multivariate testing, test implementation, results analysis, avoiding common pitfalls, sequential testing, and experimentation platforms.
npx skills add majiayu000/claude-skill-registry --skill ab-testing-jh9282026-manus --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# A/B Testing Design and analyze controlled experiments to make data-driven decisions about product changes and optimizations. ## Overview A/B testing (split testing) is a rigorous method for comparing two or more variants to determine which performs better on a defined metric. This skill covers statistical foundations, experimental design principles, implementation strategies, and analysis techniques for running effective experiments. ## A/B Testing Fundamentals ### Core Concepts **Control (A)**: Current version or baseline **Variant (B)**: New version being tested **Randomization**: Users randomly assigned to control or variant **Metric**: Quantifiable measure of success (conversion rate, revenue, engagement) **Statistical Significance**: Confidence that difference is not due to chance ### When to Use A/B Testing **Good Use Cases**: - Testing website/app design changes - Optimizing email subject lines or content - Comparing pricing strategies - Evaluating feature changes - Testing marketing messages **Not Suitable For**: - Low-traffic pages (insufficient sample size) - Long-term strategic decisions - Understanding "why" (use qualitative research) - Testing many changes simultaneo
- Overview
- A/B Testing Fundamentals
- Core Concepts
- When to Use A/B Testing
- Experimental Design
- Hypothesis Formulation
- Sample Size Calculation
- Test Duration
- Statistical Analysis
- Hypothesis Testing
- Confidence Intervals
- Statistical Tests
- Common Pitfalls and Solutions
- Multiple Comparisons Problem
What does the ab-testing skill do?
Design and analyze A/B tests and controlled experiments for data-driven decisions. Use for: experiment design, hypothesis formulation, sample size calculation, statistical significance testing, multivariate testing, test implementation, results analysis, avoiding common pitfalls, sequential testing, and experimentation platforms.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ab-testing-jh9282026-manus --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.