Validate A/B test results and experiment design
statistical-analystskillsetup L1★17,464
alirezarezvani/claude-skills ↗What it does
Run hypothesis tests and analyze A/B experiment results
Best for
Rigorously validating A/B test results when business decisions depend on statistical confidence.
Inputs
- · JSON payload
- · CSV or data file
- · CLI arguments
- · Form data
Outputs
- · Structured result (JSON/NDJSON)
- · Report/log
- · Dashboard/table
- · Result object
Requires
- · Python CLI
Failure modes
- · Resource collision/lock conflict
Trust signals
- · Test cases documented
- · Open source repository
- · Versioned release