UA Ledger · Measurement Lab · draft for review
Synthetic teaching inputs. No real campaign results or industry defaults. Change the values to inspect the model. Calculations run locally; this page sends no data and does not retain inputs after closing.
Count one eligible return outcome per independent install and preserve the total sample. The score-interval formula adjusts the centre and width using the sample size, observed proportion and squared quantile. The supplied artifact shows the arithmetic rather than rounding a small cohort to a confident whole percentage. For clustered or dependent observations, this model is not the correct uncertainty calculation.
Only n varies; all other inputs are held constant. This is not a probability range.
100*x/n100*(x/n+1.96**2/(2*n)-1.96*Math.sqrt((x/n*(1-x/n)+1.96**2/(4*n))/n))/(1+1.96**2/n)100*(x/n+1.96**2/(2*n)+1.96*Math.sqrt((x/n*(1-x/n)+1.96**2/(4*n))/n))/(1+1.96**2/n)Additional constraints: (x<=n). The field minimums also apply.
Use a pre-specified analysis plan for comparisons or repeated monitoring. Overlapping or non-overlapping intervals alone are not a complete test of the difference between two campaign treatments.
Confidence intervals for a proportion · primary documentation checked 19 September 2026.