# Inspecting assumption of homoscedasticity

Using a Fligner test to infer about the respect of the assumption of homoscedasticity is not very smart given that the Fligner test tests to the null that there is no difference of variance between the groups. This will wrongly favors small sample size. As it has been said by @Michael Mayer here.

How can we further investigate if the assumption of homoscedasticity is respected?

Is it worth plotting the model's residuals versus the fitted values? Below lines are R coded:

m = aov(myFormula, myData)
plot(residuals(m), m\$fit)


I don't have much experience in statistics and it seems rather hard for me to decide from this plot whether the assumption of homoscedasticity is respected. What else can I do?

• If you plot(m) you should get 4 plots, including a scale-location plot, which should be easier to interpret - if the mean of the scale location plot clearly changes, you don't have homoskedasticity. – Glen_b Nov 20 '13 at 1:37