# Adjusted significance level in SPSS for Kruskal Wallis Post Hoc Test - Bonferroni adjustment

I am making a pairwise comparison using Dunn's post hoc test with Bonferroni correction. However, I am a bit confused on the interpretation of the adjusted significance on SPSS. I am making 10 pairwise comparisons, and thus my assumption is that the adjusted significance will be 0.005 (0.05/10). However, my question is when seeing the pairwise comparisons table on SPSS do I have to take this calculation that I made into consideration when looking at the adjusted significance? This is an example:

Sample 1 - Sample 2 Sig. Adj. Sig.
1-4 0.000 0.008
1-7 0.000 0.005
4-7 0.895 1.000

According to the table above, my understanding is that observations 1-4 and 4-7 are not significant different as the adj. sig is higher than 0.005 (what I calculated)? Am I wrong? Thank you in advance.

"Adj. sig" looks like "q values," where instead of adjusting the rejection criterion $$\alpha$$ by dividing it by the number of comparisons, they multiple the p value by the number of comparisons. (You get incoherent gibberish when doing so, because you end up with "probabilities" greater than 1, but since you would be very far from rejecting with the unadjusted p values anyway, this is tolerated in practice.)
To recap: compare unadjusted p values to $$\frac{\alpha}{10}$$. This will give the same rejection decisions as comparing adjusted p values of $$\alpha$$.
• @Louise Two unadjusted p values are less that $\frac{0.05}{10} = 0.005$. And two of the adjusted p values from the same two tests are less than $0.05$. Oct 10, 2021 at 15:21