If you want to assess the strength of your hypothesis given the evidence, you must also assess the strength of the evidence given your hypothesis. In the face of uncertainty, a Bayesian asks three questions: How confident am I in the truth of my initial belief? On the assumption that my original belief is true, how confident am I that the new evidence is accurate? And whether or not my original belief is true, how confident am I that the new evidence is accurate? One proto-Bayesian, David Hume, underlined the importance of considering evidentiary probability properly when he questioned the authority of religious hearsay: one shouldn’t trust the supposed evidence for a miracle, he argued, unless it would be even more miraculous if the report were untrue.
Now this doesn't exactly follow the logic of the article, but it made me think of something else I read a few years ago in a book I can't remember the name of. It said that really it seemed more miraculous that Jesus could die than that he rose from the dead. That God, who created life, from whom all life comes, could cease to be alive, could step outside of life into death: well, that seemed much more preposterous than coming back.
As for thinking through whether it would be more miraculous that he didn't come back to life, as I suppose this specific logic would want me to do, well, maybe miraculous is the wrong word. Wouldn't it be more unthinkable if he stayed dead, if you believe he was really God?
Anyway, fun stuff to think through.
(p.s. Feel free to point out any gaping holes in logic, on my part or otherwise--I just sort of threw this together and besides, it's the conversation around this that I'm more interested in. What do you think?)