Analytic Calculation of Covariance between Cosmological Parameters from Correlated Data Sets, with an Application to SPTpol

Consistency checks of cosmological data sets are an important tool because they may suggest systematic errors or the type of modifications to ?CDM necessary to resolve current tensions. In this work, we derive an analytic method for calculating the level of correlations between model parameters from two correlated cosmological data sets, which complements more computationally expensive simulations. This method is an extension of the Fisher analysis that assumes a Gaussian likelihood and a known data covariance matrix. We apply this method to the South Pole Telescope Polarimeter (SPTpol) temperature and polarization cosmic microwave background (CMB) spectra (TE and EE). We find weak correlations between ?CDM parameters with a 9% correlation between the TE-only and EE-only constraints on H-0 and a 25% and 32% correlation for log(A(s)) and n(s) respectively. The TE-EE parameter differences are consistent with zero, with a probability to exceed of 0.53. Using simulations we show that this test is independent of the consistency of the SPTpol TE and EE band powers with the best-fit ?CDM model spectra. Despite the negative correlations between the TE and EE power spectra, the correlations between TE-only and EE-only ?CDM parameters are positive. Ignoring correlations in the TT-TE and TE-EE comparisons biases the chi(2) low, artificially making parameters look more consistent. Therefore, we conclude that these correlations need to be accounted for when performing internal consistency checks of the TT versus TE versus EE power spectra for future CMB analyses.