Hostname: page-component-745bb68f8f-mzp66 Total loading time: 0 Render date: 2025-01-08T09:22:28.566Z Has data issue: false hasContentIssue false

The Significance of Difference Between Means Without Reference to the Frequency Distribution Function

Published online by Cambridge University Press:  01 January 2025

Leon Festinger*
Affiliation:
Research Center for Group Dynamics, Massachusetts Institute of Technology

Abstract

Most existing tests for significance of difference between means require specific assumptions concerning the distribution function in the parent population. The need for a test which can be applied without making any such assumption is stressed. Such a statistical test is derived. The application of the test involves converting scores to rank orders. The exact probabilities may then be calculated for specified differences between samples by means of which the null hypothesis may be tested. The application of the test is simple and requires a minimum of calculation. The test loses in precision because of the conversion to rank orders but gains in generality since it may be safely used with any kind of distribution.

Type
Original Paper
Copyright
Copyright © 1946 The Psychometric Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

This study was started at the Iowa Child Welfare Research Station of the State University of Iowa. I should like to express my gratitude for the help I received there.

References

Dixon, W. J. A criterion for testing the hypothesis that two samples are from the same population. Annals math. Stat., 1940, 11, 199204.CrossRefGoogle Scholar
Festinger, L. An exact test of significance for means of samples from populations with an exponential frequency distribution. Psychometrika, 1943, 8, 153160.CrossRefGoogle Scholar
Festinger, L. A statistical test for means of samples from skew populations, 1943, 8, 205210.Google Scholar
Holzinger, K. J. and Church, A. E. R. On the means of samples from a U-shaped population. Biometrika, 1928, 20a, 361388.CrossRefGoogle Scholar
Neyman, J. and Pearson, E. S. On the use and interpretation of certain test criteria for purposes of statistical inference. Biometrika, 1928, 20a, 175240.Google Scholar
Pearson, E. S. and Adyanthaya, N. K. The distribution of frequency constants in small samples from non-normal symmetrical and skew populations. Biometrika, 1929, 21, 259286.CrossRefGoogle Scholar
Pearson, K., Stouffer, S. A. and David, F. N. Further application in statistics of the TM(x) Bessel Function. Biometrika, 1932, 24, 293350.Google Scholar
Rider, P. R. On small samples from certain non-normal universes. Annals math. Stat., 1931, 2, 4865.CrossRefGoogle Scholar
Rider, P. R. On the distribution of the ratio of mean to standard deviation in small samples from non-normal universes. Biometrika, 1929, 21, 124143.CrossRefGoogle Scholar
Sophister, . Discussion of small samples drawn from an infinite skew population. Biometrika, 1928, 20a, 389423.CrossRefGoogle Scholar
Wolf, A. and Wolfowitz, J. On a test whether two samples are from the same population. Annals math. Stat., 1940, 11, 147162.Google Scholar