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.