This is a general statistics question so I'm sorry if its outside the field of r help.
 
Anyway, I have a suite of female and male traits and I have made a matrix of correlation coefficients using rcorr(). This results in a 6 by 6 matrix like this..
 
[1] 0.11287990 0.20441361 0.23837442 0.04713234 0.04331637 0.01461611
 [7] 0.22627981 0.11720108 0.14252307 0.19531625 0.29989953 0.09989502
[13] 0.03888750 0.11157971 0.02693303 0.01373447 0.08913154 0.06770636
[19] 0.01984838 0.10047978 0.05200218 0.16317234 0.26999963 0.10412373
[25] 0.06269722 0.14366454 0.13123054 0.27550149 0.43863848 0.28909831
[31] 0.01454485 0.02551081 0.05645427 0.15819397 0.16508231 0.12399349

I want to test 2 hypotheses
 
1) is there a pattern to the matrix, does it differ from random?
2) do the top left and bottom right quadrants differ from the other 2 quadrants and if so, which one has the highest values of r2.
 
I have read alot about permutation tests, bootstrapping and mantel tests but cant decide which is best in this situation? 
 
Could anyone please provide a starting point?
 
Thankyou in advance, Simon

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