Event Title

Misapplications of the Wilcoxon-Mann-Whitney Test

Research Mentor(s)

Noguchi, Kimihiro

Description

Experimental designs using two or more treatments frequently arise in many fields of study, from medicine to psychology to policymaking. The use of rank-based nonparametric methods is recommended for analyzing effects in these designs as the observed data typically come from non-normal distributions with possibly several outliers. One of the most commonly used technique when conducting nonparametric analysis on two independent treatment groups is the Wilcoxon-Mann-Whitney (WMW) test, which is often thought of as a comparison between population medians of the two treatment groups. It can be shown that the WMW test actually fails as a comparison of medians and is better suited to be a comparison of stochastic superiority between these two groups.

Document Type

Event

Start Date

May 2020

End Date

May 2020

Department

Statistics, Mathematics

Genre/Form

student projects, posters

Type

Image

Rights

Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.

Language

English

Format

application/pdf

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May 18th, 9:00 AM May 22nd, 5:00 PM

Misapplications of the Wilcoxon-Mann-Whitney Test

Experimental designs using two or more treatments frequently arise in many fields of study, from medicine to psychology to policymaking. The use of rank-based nonparametric methods is recommended for analyzing effects in these designs as the observed data typically come from non-normal distributions with possibly several outliers. One of the most commonly used technique when conducting nonparametric analysis on two independent treatment groups is the Wilcoxon-Mann-Whitney (WMW) test, which is often thought of as a comparison between population medians of the two treatment groups. It can be shown that the WMW test actually fails as a comparison of medians and is better suited to be a comparison of stochastic superiority between these two groups.