Testing for calibration systematics in the EDGES low-band data using
  Bayesian model selection
  Cosmic Dawn, when the first stars and proto-galaxies began to form, is
commonly expected to be accompanied by an absorption signature at radio
frequencies. This feature arises as Lyman-$\alpha$ photons emitted by these
first luminous objects couple the 21 cm excitation temperature of intergalactic
hydrogen gas to its kinetic temperature, driving it into absorption relative to
the CMB. The detailed properties of this absorption profile encode powerful
information about the physics of Cosmic Dawn. Recently, Bowman et al. analysed
data from the EDGES low-band radio antenna and found an unexpectedly deep
absorption profile centred at 78 MHz, which could be a detection of this
signature. Their specific analysis fit their measurements using a polynomial
foreground model, a flattened Gaussian absorption profile and a white noise
model; we argue that a more accurate model, that includes a detailed noise
model and accounting for the effects of plausible calibration errors, is
essential for describing the EDGES data set. We perform a Bayesian
evidence-based comparison of models of the EDGES low-band data set and find
that those incorporating these additional components are decisively preferred.
The subset of the best fitting models of the data that include a global signal
favour an amplitude consistent with standard cosmological assumptions (A < 209
mK). However, there is not strong evidence to favour models of the data
including a global 21 cm signal over those without one. Ultimately, we find
that the derivation of robust constraints on astrophysics from the data is
limited by the presence of systematics.
