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NLaSpina
Level I

Homogeneity of variance & non-parametric tests

Is homogeneity of variance required for running a Wilcoxon or Kruskal-wallis test? If so, what test can I run if my data fails this assumption?

 

My objective is to see if there is a statistically significant difference between "seasons" (7 levels, i.e. - May 2011, August 2011, etc.) in terms of standardized abundance (n/m^3). We sampled the same location each month and year.

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Re: Homogeneity of variance & non-parametric tests

Just to be clear, the non-parametric tests address any difference in populations without reference to a specific parameter, such as the location, shape, or scale. So there is no assumption of homoscedasticity.

Learn it once, use it forever!

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Re: Homogeneity of variance & non-parametric tests

Just to be clear, the non-parametric tests address any difference in populations without reference to a specific parameter, such as the location, shape, or scale. So there is no assumption of homoscedasticity.

Learn it once, use it forever!

View solution in original post

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NLaSpina
Level I

Re: Homogeneity of variance & non-parametric tests

Perfect, thank you!
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