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We present mass and mass profile estimates for the Milky Way Galaxy using theBayesian analysis developed by Eadie et al (2015b) and using globular clusters(GCs) as tracers of the Galactic potential. The dark matter and GCs are assumedto follow different spatial distributions; we assume power-law model profilesand use the model distribution functions described in Evans et al. (1997);Deason et al (2011, 2012a). We explore the relationships between assumptionsabout model parameters and how these assumptions affect mass profile estimates.We also explore how using subsamples of the GC population beyond certain radiiaffect mass estimates. After exploring the posterior distributions of differentparameter assumption scenarios, we conclude that a conservative estimate of theGalaxy's mass within 125kpc is $5.22\times10^{11} M_{\odot}$, with a $50\%$probability region of $(4.79, 5.63) \times10^{11} M_{\odot}$. Extrapolating outto the virial radius, we obtain a virial mass for the Milky Way of$6.82\times10^{11} M_{\odot}$ with $50\%$ credible region of $(6.06, 7.53)\times 10^{11} M_{\odot}$ ($r_{vir}=185^{+7}_{-7}$kpc). If we consider only theGCs beyond 10kpc, then the virial mass is $9.02~(5.69, 10.86) \times 10^{11}M_{\odot}$ ($r_{vir}=198^{+19}_{-24}$kpc). We also arrive at an estimate of thevelocity anisotropy parameter $\beta$ of the GC population, which is$\beta=0.28$ with a $50\%$ credible region (0.21, 0.35). Interestingly, themass estimates are sensitive to both the dark matter halo potential and visiblematter tracer parameters, but are not very sensitive to the anisotropyparameter.

Bayesian Mass Estimates of the Milky Way II: The dark and light sides of parameter assumptions