Methods · Robust & resampling methods · Density estimation

Empirical Distribution Function with Confidence Band

The empirical distribution function is the step function giving the proportion of observations at or below each value, shown here with a Dvoretzky–Kiefer–Wolfowitz simultaneous confidence band.

각 값 이하인 관측의 비율을 나타내는 계단 함수인 경험분포함수를 Dvoretzky–Kiefer–Wolfowitz 동시 신뢰대와 함께 추정하는 방법입니다.

I want to show the whole distribution of waiting times with uncertainty, not just the mean. How do I put a confidence band around the cumulative distribution?

평균만이 아니라 대기 시간 분포 전체를 불확실성과 함께 보여 주고 싶어요. 누적분포에 신뢰대를 어떻게 그리나요?

Plot the empirical distribution function and add the Dvoretzky–Kiefer–Wolfowitz band F̂(x) ± ε with ε = √(ln(2/α)/(2n)), which covers the true distribution function at all x simultaneously with probability at least 1 − α. Quantiles can be read off the curve, and reading the band edges gives distribution-free intervals for them.

When to use Empirical Distribution Function with Confidence Band

When to use something else

Assumptions and requirements

What the analysis reports

How to report it

The empirical distribution function of [variable] (n = [value]) was estimated with a 95% Dvoretzky–Kiefer–Wolfowitz simultaneous band (ε = [value]); the median was [value] (band-based interval [[value], [value]]).

Related methods

Run Empirical Distribution Function with Confidence Band on Quorant

Data you need
a table (CSV or Excel) with an outcome variable
Price
150 credits for one analysis up to 10,000 rows (complexity level 1); larger or wider data costs more. Optional methodologist review: 900 credits.
Checking
Checked by property tests in every deployment
Before you pay
A free pre-analysis diagnosis checks your data and gives an exact quote; nothing is deducted until you approve it.

Method ID Q13006 · Reviewed 2026-10-25