  In a Perspectives article in Science, Bradley Efron concludes that Bayesian
calculations cannot be uncritically accepted when using uninformative priors.
We argue that this conclusion is problematic because Efron's example does not
use data, hence it is not Bayesian statistics; his priors make little sense and
are not uninformative; and using the available data point and an uninformative
prior actually leads to a reasonable posterior distribution.
