  The application of Bayesian techniques to astronomical data is generally
non-trivial because the fitting parameters can be strongly degenerated and the
formal uncertainties are themselves uncertain. An example is provided by the
contradictory claims over the presence or absence of a universal acceleration
scale (g$_\dagger$) in galaxies based on Bayesian fits to rotation curves. To
illustrate the situation, we present an analysis in which the Newtonian
gravitational constant $G_N$ is allowed to vary from galaxy to galaxy when
fitting rotation curves from the SPARC database, in analogy to $g_{\dagger}$ in
the recently debated Bayesian analyses. When imposing flat priors on $G_N$, we
obtain a wide distribution of $G_N$ which, taken at face value, would rule out
$G_N$ as a universal constant with high statistical confidence. However,
imposing an empirically motivated log-normal prior returns a virtually constant
$G_N$ with no sacrifice in fit quality. This implies that the inference of a
variable $G_N$ (or g$_{\dagger}$) is the result of the combined effect of
parameter degeneracies and unavoidable uncertainties in the error model. When
these effects are taken into account, the SPARC data are consistent with a
constant $G_{\rm N}$ (and constant $g_\dagger$).
