  Theoretical uncertainties in the predictions of relativistic mean-field
models are estimated using a chi-square minimization procedure that is
implemented by studying the small oscillations around the chi-square minimum.
By diagonalizing the matrix of second derivatives, one gains access to a wealth
of information---in the form of powerful correlations---that would normally
remain hidden. We illustrate the power of the {\sl covariance analysis} by
using two relativistic mean-field models: (a) the original linear Walecka model
and (b) the accurately calibrated FSUGold parametrization. In addition to
providing meaningful theoretical uncertainties for both model parameters and
predicted observables, the covariance analysis establishes robust correlations
between physical observables. In particular, we show that whereas the
correlation coefficient between the slope of the symmetry energy and the
neutron-skin thickness of Lead is indeed very large, a 1% measurement of the
neutron radius of Lead may only be able to constrain the slope of the symmetry
energy to about 30%.
