Hi

I have a question regarding statistical tests.

Assume that I have to run a program 5 times (5 iterations) and each time it gives me some data:

Iteration 1 : class1: 0.0, class2: 0.5, class3: 0.5, class4: 0.0
Iteration 2 : class1: 1.0, class2: 0.0, class3: 0.0, class4: 0.0
Iteration 3 : class1: 0.5, class2: 0.5, class3: 0.0, class4: 0.0
Iteration 4 : class1: 0.0, class2: 1.0, class3: 0.0, class4: 0.0
Iteration 5 : class1: 0.0, class2: 0.0, class3: 1.0, class4: 0.0


I need to do a statistical test to know which class (or set) is significantly different from the other classes (or sets).


My four sets will be:
1- class1 values from all iterations = (0.0, 1.0, 0.5, 0.0, 0.0)
2- class2 values from all iterations = (0.5, 0.0, 0.5, 1.0, 0.0)
3- class3 values from all iterations = (0.5, 0.0, 0.0, 0.0, 1.0)
4- class4 values from all iterations = (0.0, 0.0, 0.0, 0.0, 0.0)


I thought to use "One-way ANOVA" then "Tukey's test" exactly like here: http://cleverowl.uk/2015/07/01/using...are-data-sets/

But the problem is that my data is kind of dependent.You can see each iteration is added up to 1. for example, in iteration1, 0.0 + 0.5 + 0.5 = 1. In iteration2, 1.0 + 0.0 + 0.0 = 1 and so on.
So, which is the best statistical test I can use in my situation?

Thank you