ab-testing-statistics
CommunityMake statistically sound A/B conclusions.
Data & Analytics#statistics#ab-testing#hypothesis-testing#effect-size#p-value#power-analysis#a/b-test
AuthorKaiserWhoLearns
Version1.0.0
Installs0
System Documentation
What problem does it solve?
An experienced data analyst needs a consistent, statistically valid method for interpreting A/B test results, ensuring correct test selection and accurate conclusions.
Core Features & Use Cases
- Select appropriate tests for binary metrics (two-proportion z-test) and continuous metrics (Welch's t-test).
- Perform multiple comparison corrections and calculate effect sizes and relative lift.
- Plan experiments with power analysis to determine required sample sizes and guide reporting.
Quick Start
Run the recommended A/B analysis on your experiment data and interpret the results.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 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-testing-statistics Download link: https://github.com/KaiserWhoLearns/skillsbench/archive/main.zip#ab-testing-statistics Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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