Methods · Hypothesis testing · Outlier detection

Adjusted Boxplot Outlier Detection (Medcouple)

The adjusted boxplot flags outliers with fences that are widened on the skewed side according to the medcouple, a robust measure of skewness, so skewed data are not over-flagged.

조정 상자그림은 강건한 왜도 지표인 medcouple에 따라 치우친 쪽 울타리를 넓혀, 치우친 자료에서 정상값을 이상치로 과하게 잡지 않도록 하는 이상치 탐지법입니다.

My income variable is right-skewed and the usual boxplot rule marks too many high values as outliers; what should I use?

소득 변수가 오른쪽으로 치우쳐서 일반 상자그림 기준으로는 높은 값이 너무 많이 이상치로 잡혀요. 무엇을 써야 하나요?

The adjusted boxplot keeps the quartiles and interquartile range of the usual rule but multiplies the fence lengths by exponential factors of the medcouple, extending the fence on the long tail and shortening it on the short tail. For symmetric data the medcouple is zero and the rule is the same as Tukey's boxplot.

When to use Adjusted Boxplot Outlier Detection (Medcouple)

When to use something else

Assumptions and requirements

What the analysis reports

How to report it

Using the adjusted boxplot rule (MC = [value]; fences [[value], [value]]), [value] of [N] observations were flagged as outliers, compared with [value] under the Tukey rule.

Related methods

Run Adjusted Boxplot Outlier Detection (Medcouple) on Quorant

Data you need
a table (CSV or Excel) with an outcome variable
Price
250 credits for one analysis up to 10,000 rows (complexity level 2); larger or wider data costs more. Optional methodologist review: 1200 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 Q11085 · Reviewed 2026-10-25