# Is Friedman's test for dependent samples or not?

Which test should I use for hypothesis testing on more than two dependent non-parametric data?

The Friedman's test seems to be the option, as I have read in several books and webs, but, when I look for it on MatLab, here, it says:

Friedman's test makes the following assumptions about the data in X:

All data come from populations having the same continuous distribution, apart from possibly different locations due to column and row effects.

All observations are mutually independent.

Should I trust MatLab information? or is it that "observations being mutually independent" is different to independent samples? What does that mean then?

Should I then use Friedman's test with my dependent data? I am really confused.

• Conditional on the blocking factor, they're independent. If you don't condition on it, they're dependent. – Glen_b -Reinstate Monica Sep 3 '16 at 15:54

There is nothing wrong in Matlab's description, mutually independent just means each pair of your observations are independent.