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MODULE 7: EVALUATION & BENCHMARKING · SCENE 21

Reporting Uncertainty: CIs & Elo

Confidence-interval half-widths, win-rate to Elo conversion, and why single-point leaderboard scores mislead.

ITEMS nACC70.0% ± 4.0 (95% CI)
Model A 71.2% ± 1.5Model B 69.8% ± 4.01.96 · √(p(1−p)/n) — AT n=500: ±4.0 PTS. A 1.4-PT GAP INSIDE OVERLAPPING CIs IS NOT EVIDENCE.

At 500 items the interval is ±4.0 points — most adjacent-leaderboard gaps are noise. Claim improvement only when intervals separate.
GO DEEPER: CONFIDENCE INTERVALS IN THE EVALUATION WORLD →

TECHNICAL BREAKDOWNModule 7: Evaluation & Benchmarking

Honest reporting: confidence intervals on every score

A benchmark score without an interval is a point estimate pretending to be a fact. On a 500-item benchmark, a 70% score carries a ±4-point 95% CI — enough to make most adjacent-leaderboard comparisons meaningless.

Normal Approximation

CI half-width = 1.96·√(p(1−p)/n). It shrinks with √n: doubling items improves precision by only 41%.

Overlapping Intervals

Model A at 71.2 ± 1.5 vs Model B at 69.8 ± 1.6: the difference is inside the noise. Claim improvement only when intervals separate.

Paired Tests

McNemar's test on the same items is sharper than comparing two independent CIs — items both models get right carry no information about the difference.

MATHEMATICAL FORMULATION · CI HALF-WIDTH
h = 1.96 · √( p(1−p) / n ), e.g. p=0.7, n=500 → h ≈ ±0.040

70% on 500 items is 70% ± 4.0 points at 95% confidence. Beating a rival by 1.5 points on that benchmark is not evidence of anything.

REAL-WORLD PRODUCTION ENGINEERING
  • Publish n and the interval next to every headline number — the HELM and lm-eval-harness conventions make this near-default in serious reports.
  • For pass@k and small-sample reasoning evals, use bootstrap CIs; the normal approximation is poor near 0/1 accuracy.