I am comparing measurements of 12 different groups to one another. My distributions are not normal and my Levene's test is significant - even after data transformation. I am therefore doing a Kruskal-Wallis instead of a one way ANOVA.
I have done the Kruskal-Wallis and the pair-wise comparisons available in the latest version of SPSS. They all look fine and seem to match the plots I have made. My concern is the output - the Chi squared value is huge.
As an example - I am comparing all of the lengths to each other and get the following:
Chi-Squared: 624.453 DF: 11 Asymp sig: .000
The widths gives a similar Chi Squared value of just over 400. These values seem very large - are they wrong? There is quite a lot of variation in my groups, but not an absurd amount. Some range from 1-1000 nanometers, other groups hit the 3-4000 nanometers. Is this why my Chi-squared value is so high? I am not even sure if it should be a concern to me?
This is for my final year project and SPSS is all I can use.