First consider the idea that the scientist who runs the Bayesian analysis provides the prior probability herself. One obvious problem with this idea is that the opinion of the scientist might not be precise enough for a determination of a full prior distribution. It does not seem realistic to suppose that the scientist can transform her opinion into a single real-valued function over the model, especially not if the model itself consists of a continuum of hypotheses. But the more pressing problem is that different scientists will provide different prior distributions, and that these different priors will lead to different statistical results. In other words, Bayesian statistical inference introduces an inevitable subjective component into scientific method.