Statnote 5: Is one set of data more variable than another?


Autoria(s): Hilton, Anthony; Armstrong, Richard A.
Data(s)

01/06/2006

Resumo

There may be circumstances where it is necessary for microbiologists to compare variances rather than means, e,g., in analysing data from experiments to determine whether a particular treatment alters the degree of variability or testing the assumption of homogeneity of variance prior to other statistical tests. All of the tests described in this Statnote have their limitations. Bartlett’s test may be too sensitive but Levene’s and the Brown-Forsythe tests also have problems. We would recommend the use of the variance-ratio test to compare two variances and the careful application of Bartlett’s test if there are more than two groups. Considering that these tests are not particularly robust, it should be remembered that the homogeneity of variance assumption is usually the least important of those considered when carrying out an ANOVA. If there is concern about this assumption and especially if the other assumptions of the analysis are also not likely to be met, e.g., lack of normality or non additivity of treatment effects then it may be better either to transform the data or to carry out a non-parametric test on the data.

Formato

application/pdf

Identificador

http://eprints.aston.ac.uk/9316/1/Statnote_5.pdf

Hilton, Anthony and Armstrong, Richard A. (2006). Statnote 5: Is one set of data more variable than another? Microbiologist, 2006 , pp. 34-36.

Relação

http://eprints.aston.ac.uk/9316/

Tipo

Article

NonPeerReviewed