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Related Experiment Videos

The Fisher-Pitman permutation test when testing for differences in mean and variance.

Markus Neuhäuser1, Bryan F J Manly

  • 1Department of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin, NZ. mneuhaus@maths.otago.ac.nz

Psychological Reports
|April 14, 2004
PubMed
Summary

The Fisher-Pitman permutation test detects any sample difference, not just means. A new two-stage method separately tests for mean or variance differences in nonnormal distributions.

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Area of Science:

  • Statistics
  • Statistical inference
  • Nonparametric statistics

Background:

  • The Fisher-Pitman permutation test is a versatile tool for detecting any difference between two samples.
  • However, a significant result does not isolate whether the difference lies in the means or variances.
  • Separate testing for mean and variance differences is often necessary.

Purpose of the Study:

  • To introduce a novel two-stage procedure for distinguishing between mean and variance differences in two samples.
  • To provide a method applicable to nonnormal distributions with potentially unequal variances.

Main Methods:

  • A two-stage procedure is proposed to first identify if any difference exists, and then to determine if it is in the means or variances.
  • The method is designed for robustness against nonnormality and unequal variances.

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Main Results:

  • The presented procedure allows for the separate and specific testing of differences in means and variances.
  • It offers a solution for situations where traditional tests may be inadequate due to distribution assumptions.

Conclusions:

  • The two-stage procedure effectively differentiates between mean and variance differences in samples from nonnormal distributions.
  • This method enhances statistical inference by providing more specific insights into sample variations.