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Specialized skill for statistical experiment design and analysis capabilities. Enables product teams to design rigorous experiments, calculate sample sizes, and interpret results with statistical confidence.
Capabilities
Experiment Design
Calculate required sample sizes for experiments
Design experiment variants and hypotheses
Define success metrics and guardrail metrics
Create experiment documentation templates
Design multi-variant tests (A/B/n)
Plan sequential and Bayesian experiments
Statistical Analysis
Validate statistical significance of results
Calculate practical significance and effect sizes
Detect interaction effects and segments
Perform power analysis
Calculate confidence intervals
Handle multiple comparison corrections
Decision Support
Recommend ship/iterate/kill decisions
Identify segment-specific impacts
Assess long-term vs short-term effects
Generate experiment reports
Track experiment velocity metrics
Target Processes
This skill integrates with the following processes:
product-market-fit.js - Validation experiments for PMF hypotheses
{"type":"object","properties":{"experimentType":{"type":"string","enum":["ab","multivariate","sequential","bandit"],"description":"Type of experiment to design"},"hypothesis":{"type":"string","description":"Hypothesis to test"},"primaryMetric":{"type":"object","properties":{"name":{"type":"string"},"baseline":{"type":"number"},"mde":{"type":"number","description":"Minimum detectable effect"}}},"guardrailMetrics":{"type":"array","items":{"type":"string"},"description":"Metrics that should not regress"},"trafficAllocation":{"type":"number","description":"Percentage of traffic for experiment"},"confidenceLevel":{"type":"number","default":0.95,"description":"Statistical confidence level"}},"required":["experimentType","hypothesis","primaryMetric"]}
