Solved – multiple continuous independent variables, single dependent var: which analysis

I am setting up a linear analysis of a single continuous dependent variable, with multiple (up to 11!) continuous independent variables. I am interested in doing something like an ANCOVA that will show the relative contribution and co-variation among the variables. But my understanding is that ANCOVA requires having at last one categorical variable, which my data does not have. I have already done multiple regression analysis that yields a correlation grid, but does not show covariation among variables.
Is there another analysis I should consider?
Should I force my data to fit into an ANCOVA analysis?

Here's a sample of the data for clarity.

DV      iv1     iv2     iv3     iv4     iv5     iv6 -0.34   2.05    7.77    0.00    3.91    2.23    10.80 -0.40   2.23    0.53    3.14    1.67    3.34    13.93 -0.24   6.98    2.04    2.82    9.30    2.33    13.95 -0.39   0.00    1.48    0.00    2.62    3.06    10.04 -0.32   0.79    0.00    0.00    5.51    3.94    10.24 0.24    0.00    0.00    0.00    0.00    6.15    13.85 1.58    1.34    0.00    0.00    3.41    2.20    13.05 1.07    4.05    2.99    0.00    2.89    3.47    8.09 -0.44   2.31    1.86    0.00    1.54    4.62    13.08 -0.49   2.94    2.68    0.00    10.29   1.47    11.76 

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