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Ab Test Analyzer

Listed
jeremylongshore·vlatest·testing·MIT

Analyzes A/B test results, providing statistical significance, confidence intervals, and actionable insights for optimization.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jeremylongshore/tons-of-skills-marketplace --skill ab-test-analyzer -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jeremylongshore

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. none of the 396 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as jeremylongshore/claude-code-plugins-plus-skills.
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About this skill

What it does

This skill analyzes A/B test results and provides insights. It can determine statistical significance, calculate confidence intervals, and identify which variation performed better based on provided data. The tool aims to simplify the interpretation of experiment outcomes for faster decision making.

When to use it

  • You have run an A/B test on a website or application feature and need to understand if the results are statistically significant.
  • You want to quickly determine which variation in your A/B test performed better based on key metrics like conversion rate or click-through rate.
  • You need to calculate confidence intervals for your A/B test data to assess the reliability of the findings.
  • You're presenting A/B test results to stakeholders and require a clear, concise summary of the analysis.

Key capabilities

  • Statistical significance calculation
  • Confidence interval calculation
  • Variation performance comparison
  • Data interpretation

Example prompts

  • "Analyze this A/B test data: [paste data here]"
  • "What is the statistical significance of these results? Variation A: 10% conversion, Variation B: 12%, Total users: 1000."
  • "Calculate the confidence interval for an A/B test with a difference in means of 5 and a standard deviation of 2."

Tips & gotchas

The skill requires numerical data as input. Ensure your data is properly formatted (e.g., CSV, JSON) or clearly presented for accurate analysis.