Power-law fits to the decrease in σ_K as a function of the number of RV data points (modeled as ﹩{\sigma }_{{\rm{K}}}=1/{N}_{\mathrm{obs}}^{b}﹩, where b is the shown power-law index), sampled in 3-month intervals. The four schemes are not well differentiated, which implies that no single scheme reaches higher K/σ_K values faster than the others. In all four cases, the mean power-law fit is marginally steeper than the −0.5 value expected for the mean of a Gaussian distribution, which is probably due to fitting a small number of RV points in the early data epochs.