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In order to quantify the error budget in the measured probabilitydistribution functions of cell densities, the two-point statistics of cosmicdensities in concentric spheres is investigated. Bias functions are introducedas the ratio of their two-point correlation function to the two-pointcorrelation of the underlying dark matter distribution. They describe how celldensities are spatially correlated. They are computed here via the so-calledlarge deviation principle in the quasi-linear regime. Their large-separationlimit is presented and successfully compared to simulations for density anddensity slopes: this regime is shown to be rapidly reached allowing to getsub-percent precision for a wide range of densities and variances. Thecorresponding asymptotic limit provides an estimate of the cosmic variance ofstandard concentric cell statistics applied to finite surveys. More generally,no assumption on the separation is required for some specific moments of thetwo-point statistics, for instance when predicting the generating function ofcumulants containing any powers of concentric densities in one location and onepower of density at some arbitrary distance from the rest. This exact "oneexternal leg" cumulant generating function is used in particular to probe therate of convergence of the large-separation approximation.

The large-scale correlations of multi-cell densities and profiles, implications for cosmic variance estimates