This might be a simple question, but just wanna make sure I am on the right track: I need to compare two samples using a 1-sided t-test. The sample sizes in the two groups are unequal, but it should be ok. The crucial part is that, the data in both groups are not independent. To be more specific, I have 4 vectors, v1, v2, v3 and v4, and I calculate the pairwise angles: v12, v13, v14, v23, v24, v34. Then I put them into two groups:

Group1: v12, v34
Group2: v13, v14, v23, v24

Then I compare group 1 and 2 using one-sided two-sample t-test. This violates the independent samples assumption of t-test, right? I am considering a solution of using permutation test in the coin R pacakge (one_way() function). Is that the correct way to do? Thanks!

This might be a simple question, but just wanna make sure I am on the right track: I need to compare two samples using a 1-sided t-test. The sample sizes in the two groups are unequal, but it should be ok. The crucial part is that, the data in both groups are not independent. To be more specific, I have 4 vectors, v1, v2, v3 and v4, and I calculate the pairwise angles: v12, v13, v14, v23, v24, v34. Then I put them into two groups:

Group1: v12, v34
Group2: v13, v14, v23, v24

Then I compare group 1 and 2 using one-sided two-sample t-test. This violates the independent samples assumption of t-test, right? I am considering a solution of using permutation test in the coin R package (one_way() function). Is that the correct way to do?