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Update parametric.py - fix typo #448

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Oct 17, 2024
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Update parametric.py - fix typo #448

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2 changes: 1 addition & 1 deletion src/pingouin/parametric.py
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Expand Up @@ -1262,7 +1262,7 @@ def welch_anova(data=None, dv=None, between=None):
it is best to use the Welch ANOVA that better controls for
type I error (Liu 2015). The homogeneity of variances can be measured with
the `homoscedasticity` function. The two other assumptions of
normality and independance remain.
normality and independence remain.

The main idea of Welch ANOVA is to use a weight :math:`w_i` to reduce
the effect of unequal variances. This weight is calculated using the sample
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