Originally Posted by

**Dragan**
What I am saying is that it's going to provide the same answer..i.e. whether you test the normality assumption on the dependent variable (Y) or the error terms (e). For example, in a one-way ANOVA the linear model is: Y_ij = OverallMean + Treatment_j + error, for person *i* in treatment group *j*.

Which would be fine if we were checking for multivariate normality or something. But not if we just take the raw response and check for normality.

We can see that the raw data is NOT normally distributed (it's the mixture of two normals). But the residuals do pass a normality test.