Hi community,

In the residuals analysis, I evaluate normality and constant variance with the default graphs given in the regression analysis. However, I was wondering in which way I could test constant variance with a test that allow me to have sort of a p-value that make the situation more precise than looking at the graphs.

I am able to do it for normality, but not yet for the constance variance.

For example for the normality, I get the plot:

I can give some conclusions visually, but I also like to have a more precise description of the situation and therefore, I save the residuals and using the distribution platform (fit normal) I can get:

The shapiro-wilk test allow me to evaluate (in addition to the visual evaluation) the normality of my residuals.

I am now looking to do something similar (doing a test) for the constance variance of the residuals in addition to the residual vs predicted plot (that I add here below)

I know that in the case of conducting an Anova in the "fit y by x" platform, there is the possibility of evaluating constance variance with "Lavene's test", but have not been able to do it in my case after plotting in this platform my saved residuals and saved predicted values.

Do you know if there is a way in addition to the plot to test constance variance for my residuals ?

Thanks for any help,

Julian