When talking about Friedman's test, it commonly comes accompanied by a whole name of "The Friedman's test for three or more correlated samples".
The question is, could results be valid if I apply the Friedman's test to two correlated samples? Or is it strictly mandatory to be three or more?
Considering that the data of those two samples, are completely ok to be used with Friedman's test, and most important, the two samples contain repeated measures, as follows:
popcorn = 5.5000 4.5000 3.5000 5.5000 4.5000 4.0000 6.0000 4.0000 3.0000 6.5000 5.0000 4.0000 7.0000 5.5000 5.0000 7.0000 5.0000 4.5000
"This data comes from a study of popcorn brands and popper type (Hogg 1987). The columns of the matrix popcorn are brands (Gourmet, National, and Generic). The rows are popper type (Oil and Air). The study popped a batch of each brand three times with each popper. The values are the yield in cups of popped popcorn, and using Friedman's test to determine whether the popcorn brand affects the yield of popcorn."
Would it be valid to use Friedman's to determine whether the popcorn brand affects the yield, but only for the Gourmet and National brands? Like this:
popcorn = 5.5000 4.5000 5.5000 4.5000 6.0000 4.0000 6.5000 5.0000 7.0000 5.5000 7.0000 5.0000
Reference: Data and example from here.