Statistics for Traders #43: The Agresti-Coull adjusted Wald confidence interval — the 'add 2 successes and 2 failures then use Wald' rule from AC 1998. Applied to today's slot 1 NZDUSD 2-of-11 up sample: 95% CI = [4.0%, 48.9%] — rejects fair-coin (matches yesterday's Stats #42 Wilson decision at [5.1%, 47.7%]). But on the yesterday-1 CHFJPY 0-of-4 sample, AC gives [0%, 54.6%] and DOES NOT reject where Wilson does — AC's boundary artifact at small n. AC's simplicity edge kicks in at larger n per today's PT #43 BCD 2001 recommendation.
The Agresti-Coull adjusted Wald interval, straight from Paper Trail #42’s 1998 primary source: adjusted center p̃ = (x + z²/2)/(n + z²), then Wald-style ±z·√(p̃(1-p̃)/(n+z²)). For 95%, that simplifies to “add 2 successes and 2 failures then use Wald.” Applied to today’s slot 1 NZDUSD small_miss 2-of-11 up: 95% CI = [4.0%, 48.9%]— coin-flip OUTSIDE. Matches yesterday’s Stats #42 Wilson decision at [5.1%, 47.7%]. On the older CHFJPY 0-of-4 sample, though, AC gives [0%, 54.6%]and fails-to-reject where Wilson does — AC’s small-n boundary artifact.
![95% confidence intervals on the up-rate for five Vantage samples across four methods. Rows: today's NZDUSD slot-1 2/11, today's EURNZD slot-5 9/11, 2026-09-10 CHFJPY big_miss 0/4, 2026-09-09 GBPJPY big_miss 0/4, 2026-09-10 NZDJPY small_miss 0/11. Columns: Rule of Three (Stats #40), Clopper-Pearson exact (#41), Wilson score (#42), Agresti-Coull adjusted Wald (#43 - this post). Coin-flip 0.5 marked. Intervals that REJECT 50% are colored coral, others muted. Key rows: 2/11 NZDUSD - CP fails-to-reject (upper 0.518); Wilson [0.051, 0.477] rejects; AC [0.040, 0.489] rejects. 0/4 CHFJPY - Wilson rejects [0, 0.490]; AC fails [0, 0.546]. 0/11 NZDJPY - all four methods reject at unanimity.](/insights/stats-for-traders-agresti-coull/intervals.png)
The formula and the +2/+4 rule
Agresti-Coull’s exact z² form is what today’s PT #43 BCD 2001 evaluates: p̃ = (x + z²/2)/(n + z²)then Wald-around- p̃. The AC 1998 “+2/+4” simplification substitutes z²=4 (versus the exact 3.8416 for α=0.05) to get p̃ ≈ (x + 2)/(n + 4), then Wald with SE ≈ √(p̃(1-p̃)/(n+4)). For the NZDUSD 2/11 sample:
| Form | p̃ | SE | half-width | CI on up-rate |
|---|---|---|---|---|
| exact z² (z²=3.8416) | 3.9208/14.8416 = 0.26418 | 0.11445 | 0.22432 | [0.0399, 0.4885] |
| +2/+4 simplified | 4/15 = 0.26667 | 0.11421 | 0.22385 | [0.0428, 0.4905] |
Both forms round to [4.0%, 48.9%] at 1-decimal-percent precision. The simplification is a hair wider than the exact form and always in the same direction — negligible for practical use, and the “+2/+4” rule is easier to remember when you don’t have a calculator.
Cross-method comparison on five Vantage samples
| Sample | x/n | CP (#41) | Wilson (#42) | AC (#43) |
|---|---|---|---|---|
| NZDUSD 2/11 small_miss (slot 1) | 2/11 | [2.3%, 51.8%] | [5.1%, 47.7%] R | [4.0%, 48.9%] R |
| EURNZD 9/11 small_miss (slot 5) | 9/11 | [48.2%, 97.7%] | [52.3%, 94.9%] R | [51.2%, 96.0%] R |
| CHFJPY 0/4 big_miss (2026-09-10) | 0/4 | [0%, 60.2%] | [0%, 49.0%] R | [0%, 54.6%] |
| GBPJPY 0/4 big_miss (2026-09-09) | 0/4 | [0%, 60.2%] | [0%, 49.0%] R | [0%, 54.6%] |
| NZDJPY 0/11 small_miss (2026-09-10) | 0/11 | [0%, 28.5%] R | [0%, 25.9%] R | [0%, 30.0%] R |
“R” marks a rejection of the 50% coin-flip null. Wilson and AC agree on 4 of 5 samples. The one they disagree on is n=4 unanimity (CHFJPY, GBPJPY both 0-of-4 DOWN): Wilson catches the marginal rejection with upper 49.0%; AC misses with upper 54.6%. Reason: AC is a Wald-approximation of Wilson using the adjusted center p̃ in the variance p̃(1-p̃). Wilson keeps the (1+z²/n) shrinkage factor in the denominator of its half-width; AC drops it. At n=4 that shrinkage is 1.96× — significant. At n=11 it’s 1.35×; at n=40 it’s 1.10×. AC and Wilson converge as n grows.
Which method to use — BCD 2001’s recommendation
Today’s PT #43 Brown-Cai-DasGupta 2001 recommend: Wilson OR Jeffreys prior for small n (≤40), Agresti-Coull for larger n (n > 40). AC is preferred at larger n because the +2/+4 pseudo-count effect vanishes and the simpler closed form wins on interpretability. Today’s n=11 sample is squarely in the small-n regime — Wilson or Jeffreys should be preferred, but AC still gets the right coin- flip answer here. BCD 2001 also emphasize: never use plain Wald. Coverage is chaotic even at n=100 near boundaries (their Example 1: n=100, p=0.106 gives 95.2% coverage; p=0.107 gives 91.1%).
Where this sits in the Stats interval-comparison arc
Stats #40 (2026-09-09) Rule of Three: one-sided upper for x=0 or lower for x=n unanimity samples. Stats #41 (2026-09-10) Clopper- Pearson: two-sided exact, conservative. Stats #42 (2026-09-11) Wilson: score-test inversion, tightest close-to-nominal-coverage interval for small n. Stats #43 (today) Agresti-Coull: Wald-of- adjusted-center, simple “+2/+4” rule, tie-with-Wilson at moderate n and boundary artifacts at very small n. Queue rotates to Jeffreys Beta(0.5, 0.5) prior interval (Bayesian sibling recommended by BCD 2001 alongside Wilson for small n) and Newcombe 1998 method-7 hybrid intervals for score-vs-CP head-to-head coverage-comparison follow-ups.
Verification note
All AC intervals verified against Python statsmodels.stats.proportion.proportion_confint(count, nobs, alpha=0.05, method='agresti_coull') on 2026-09-12. Wilson intervals cross-checked against method='wilson'. Clopper-Pearson exact against method='beta'. All match to 4 decimals. Chart via one-off script reusing scripts/insights-charts/svg.ts + theme.ts + sharp rasterization; not committed under scripts/.