An exact rank test for scale under normality using Helmert's transformation

W. Albers

    Research output: Contribution to journalArticleAcademic

    1 Citation (Scopus)
    134 Downloads (Pure)


    In the problem of testing equality of scale of two distributions a rank test should be preferred over the F-test if it is not sure that the distributions involved are normal. However, if in addition the distributions may also differ in location, it becomes necessary to first adjust the observations, and the rank test will then at best be asymptotically distribution-free, even if normality holds after all. In this paper it is demonstrated how using Helmert's transformation for the adjustment of the observations leads to a rank test which is exact under normality and asymptotically distribution-free otherwise.
    Original languageEnglish
    Pages (from-to)331-346
    JournalJournal of statistical planning and inference
    Publication statusPublished - 1985


    Dive into the research topics of 'An exact rank test for scale under normality using Helmert's transformation'. Together they form a unique fingerprint.

    Cite this