Figure 10.
The effect of the number of systems on the HBM results for a synthetic sample whose properties were generated with realistic uncertainties. Here, we enforced ${0< i_{\mathrm{d}}< 90^{\circ }}$ following Section 2.6.1. The panels show $\mu$ (top) and $\sigma$ (bottom) versus N for 5–150 systems. The dotted lines mark the input $\mu$ and $\sigma$ used to generate the parent alignment distribution of $0^{\circ }$ and $20^{\circ }$, respectively. The underestimation is most clearly seen in $\sigma$ at large N where uncertainties are smaller. Both $\mu$ and $\sigma$ vary around their expected values by more than their uncertainties, especially at larger N. This is likely because we assume all the individual $\alpha _n^{\prime }$ estimates are Gaussian.

The effect of the number of systems on the HBM results for a synthetic sample whose properties were generated with realistic uncertainties. Here, we enforced |${0< i_{\mathrm{d}}< 90^{\circ }}$| following Section 2.6.1. The panels show |$\mu$| (top) and |$\sigma$| (bottom) versus N for 5–150 systems. The dotted lines mark the input |$\mu$| and |$\sigma$| used to generate the parent alignment distribution of |$0^{\circ }$| and |$20^{\circ }$|⁠, respectively. The underestimation is most clearly seen in |$\sigma$| at large N where uncertainties are smaller. Both |$\mu$| and |$\sigma$| vary around their expected values by more than their uncertainties, especially at larger N. This is likely because we assume all the individual |$\alpha _n^{\prime }$| estimates are Gaussian.

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