ab-test-calculator
CommunityA/B Test Significance Calculator
Data & Analytics#conversion rate#a/b testing#sample size#power analysis#statistical significance#bayesian analysis
Authordkyazzentwatwa
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps you determine if the results of your A/B tests are statistically significant, ensuring you make data-driven decisions with confidence.
Core Features & Use Cases
- Statistical Significance Testing: Use Chi-square, Z-test, or T-test to compare conversion rates between variants.
- Sample Size & Power Analysis: Calculate the necessary sample size for your test or determine the power of an existing test.
- Bayesian Analysis: Understand the probability of one variant being better than another.
- Use Case: After running an A/B test on your website's call-to-action button, use this Skill to confirm if the observed increase in clicks for the new button is statistically significant or just due to random chance.
Quick Start
Calculate the statistical significance for an A/B test with 10000 control visitors and 500 conversions, and 10000 variant visitors with 550 conversions.
Dependency Matrix
Required Modules
scipynumpy
Components
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: ab-test-calculator Download link: https://github.com/dkyazzentwatwa/chatgpt-skills/archive/main.zip#ab-test-calculator Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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