Operations Guide
AI Statistical Significance Testing for Production Model Deployment
Production AI decisions require statistical evidence. This guide covers significance testing methodology, confidence intervals, and sample size requirements for reliable model comparisons.
Direct answer
Production AI decisions require statistical evidence. This guide covers significance testing methodology, confidence intervals, and sample size requirements for reliable model comparisons.
Fast path
- Select significance level: 90% for exploratory, 95% for standard, 99% for critical changes.
- Calculate minimum sample size: Power analysis with 80% power, effect size estimation.
- Set confidence intervals: Z-score thresholds for significance determination.
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Implementation Steps
- Select significance level: 90% for exploratory, 95% for standard, 99% for critical changes.
- Calculate minimum sample size: Power analysis with 80% power, effect size estimation.
- Set confidence intervals: Z-score thresholds for significance determination.
- Monitor overlap: If control CI overlaps treatment CI, result is not significant.
- Check effect size: Treatment mean - control mean must exceed pooled standard deviation × z-score.
- Document p-value: Threshold for rejecting null hypothesis at chosen significance level.
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