Are Non-Parametric Tests Distribution-Free,

Abstract

An increasing use is being made of non-parametric tests, i.e., tests of significance which are not based on the usual assumption that all distributions are normal. Many psychologists have assumed that when non-normality or heterogenous variance is encountered in the data, then analysis of variance by ranks, the Mann-Whitney U Test (1947), Festinger's d (1946), or some similar non-parametric technique is appropriate. The purpose of this paper is to point out that non-parametric tests also have basic assumptions which must be met, and that often the factors which bar the use of the parametric tests also violate the assumptions underlying most of the non-parametric tests.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1961
Accession Number
ADA074099

Entities

People

  • Ardie Lubin

Organizations

  • Walter Reed Army Institute of Research

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Accuracy
  • Analysis Of Variance
  • Binomials
  • Chi Square Test
  • Data Science
  • Demography
  • Information Science
  • Measurement
  • Military Research
  • Normal Distribution
  • Normality
  • Observation
  • Skewness
  • Social Sciences

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.