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WFN QUICK BRIEF · UNDER 1 MIN
The short version
MODE 2 OF 2
What the source establishes
NIST describes Wilson confidence intervals for a binomial proportion and discusses why a simple symmetric approximation can be unsuitable, especially for small samples or extreme proportions. The method uses the observed count as well as the sample size. NIST/SEMATECH — confidence intervals for proportions ↗
What the distinction changes
A percentage without its denominator conceals how much information produced it. The wider interval in the small example is a warning against turning a short winning history into a precise success-probability claim.
Questions for the next review
Obtain the full trial count, inclusion rules and dated outcomes. Record the method and its assumptions alongside any interval. A frequentist 95% confidence level describes repeated-sample coverage of the procedure; it is not a promise about the next trade or a guarantee of profit.
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WFN STORY COMPASS
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EDITORIAL ILLUSTRATIONWFN EDITION · 15 OCTOBER 2026
Editorial noteSource-based explanation with original WFN analysis. Historical records retain their original periods. Numerical examples are labelled as illustrative, not observed market data. AI-generated conceptual illustration; it does not document an actual event or product interface.
WFN REALITY LEDGER
What is on the record?
Primary-source explainer
Primary-source explainer; examples are explicitly illustrative
Primary record / reference periodWilson interval methodology; all sample counts below are illustrative
The cited material establishes the documented method or historical record. WFN analysis and illustrative calculations are labelled separately.
NIST’s proportion-interval method shows why twelve wins and twelve hundred wins provide different precision, even at the same observed rate.
01 · VERIFIED RECORD
What the source establishes
NIST describes Wilson confidence intervals for a binomial proportion and discusses why a simple symmetric approximation can be unsuitable, especially for small samples or extreme proportions. The method uses the observed count as well as the sample size. NIST/SEMATECH — confidence intervals for proportions ↗
Using that formula with z = 1.96, an illustrative 12 wins from 20 trials gives a 95% interval of approximately 38.7% to 78.1%. For 1,200 wins from 2,000 trials, the corresponding interval is approximately 57.8% to 62.1%. Both observed rates are 60%; neither dataset is claimed as real trading performance.
02 · WFN EDITORIAL ANALYSIS
What the distinction changes
A percentage without its denominator conceals how much information produced it. The wider interval in the small example is a warning against turning a short winning history into a precise success-probability claim.
An interval also does not certify the dataset. Selective reporting, dependent observations and changing conditions can undermine the model before the formula is applied. Statistical precision and evidence quality need separate reviews.
03 · WHAT TO CHECK NEXT
Questions for the next review
Obtain the full trial count, inclusion rules and dated outcomes. Record the method and its assumptions alongside any interval. A frequentist 95% confidence level describes repeated-sample coverage of the procedure; it is not a promise about the next trade or a guarantee of profit.
