Assuming Equal Variances- what to do?

#1
Hello,

On my data I have assessed whether it's parametric. The distribution is normal, however on the Levene Statistic test, it has a significance level of 0.130- which means I have to assume equal variances.

What are the next steps to take from this?
Should I just use a non-parametric test? (Kriskal-Wallis test)
Or should I carry on with a one-way anova (and if so, what other implications must I consider)

Any help will be greatly appreciated!
 

Dason

Ambassador to the humans
#2
On my data I have assessed whether it's parametric.
Data isn't parametric. Some data can be modeled by certain distributions but data is just data.
The distribution is normal, however on the Levene Statistic test, it has a significance level of 0.130- which means I have to assume equal variances.
You don't have to do anything. The p-value doesn't give conclusive evidence that there seems to be a difference in variances though. This is a good thing - life is easier when we can assume equal variances which is why what you say later puzzles me. It sounds like you think that it's a bad thing that you can assume equal variances? What gave you that impression?