  We present a robust statistical analysis of the white dwarf cooling sequence
in 47 Tucanae. We combine HST UV and optical data in the core of the cluster,
Modules for Experiments in Stellar Evolution (MESA) white dwarf cooling models,
white dwarf atmosphere models, artificial star tests, and a Markov Chain Monte
Carlo (MCMC) sampling method to fit white dwarf cooling models to our data
directly. We use a technique known as the unbinned maximum likelihood to fit
these models to our data without binning. We use these data to constrain
neutrino production and the thickness of the hydrogen layer in these white
dwarfs. The data prefer thicker hydrogen layers $(q_\mathrm{H}=3.2\e{-5})$ and
we can strongly rule out thin layers $(q_\mathrm{H}=10^{-6})$. The neutrino
rates currently in the models are consistent with the data. This analysis does
not provide a constraint on the number of neutrino species.
