completely random design, violate normality

[royer11]

--------- DESIGN OF EXPERIMENTS -----
Hello
I have a difficulty in the following case:

1. normality (0.0001)
2. constant variance
3. independence of errors

when I apply the Kolmogorov test corrected by Lilliefors (0.0001), then I reject H0 and this violates 1 test assumption.
I have now been told that I must apply the Kruskal-Wallis(non-parametric) test.
If I apply this test, does she replace Kolmogorov?
and the rest stays the same? or is there any other step I'm skipping?
because then there's ANOVA.

 

[hlsmith]

Tell us more about your data, study context, and sample size.

 

[royer11]

Tell us more about your data, study context, and sample size.

it's a book problem "Design and Analysis of experiments 9th edition by Montgomery " chapter 3 page 130, problem 3.32

 

[Karabiner]

normality (0.0001)

Please keep in mind that for oneway analysis of variance
not the unconditional dependent variable should be
normally distributed, but the residuals from the model.

I have now been told that I must apply the Kruskal-Wallis(non-parametric) test.

Who told you so, and why?

If I apply this test, does she replace Kolmogorov?

It does replace the usual oneway analysis of variance, if sample size
is small and/or crucial assumtions of the ANOVA are violated.

I does not use the original values, but the values transformed
into ranks (here, from 1 to 20).

With kind regards

Karabiner

 

[royer11]

Who told you so, and why?

Hello
A teacher told me that if the assumption of normality of errors is not met, then I would use kruskal wallis as an alternative. How would it really be?

 

[Karabiner]

I was just curious. Since normality of errors was analysed (not normality of the dependent variable), and sample size is small, the Kruskal-Wallis seems like a defensible alternative.

With kind regards

Karabiner

 

[royer11]

tank you