I concluded that the probability the resurrection of Jesus happened lies within a 72% likelihood that it occurred. I thought that was a bit low myself, my biggest interfering factor was the possibility of living in an open system multiverse. I would like to see some more evaluation on the role and probabilities when open systems are considered as an objection to the resurrection. An abstract from my [non-exhaustive] recent paper titled “An Application of Bayes’s Theorem to the Case for the Historicity of the Resurrection of Jesus“:
Thomas Bayes’s theorem, in probability theory, is a rule for evaluating the conditional probability of two or more mutually exclusive and jointly exhaustive events. The conditional probability of an event is the probability of that event happening given that another event has already happened. The theorem may be expressed as:
What the solution [P(h|e&k)] represents is the probability of the hypothesis in question is given the evidence and the background information. The numerator [P(e|h&k) P(h|k)] is the probability of the product of evidence and background knowledge and the background knowledge alone. The denominator [P(e|k)] is the probability of the event with the evidence alone. Each factor involved is assigned a probability between 0 and 1 with 0 as impossible and 1 being completely certain.
When this theorem is applied to the historicity of the resurrection of Jesus the hypothesis in question is that God raised Jesus from the dead. The evidence for the resurrection will be Gary Habermas’ minimal facts approach. The background knowledge will be commonly accepted dates, the actual existence and crucifixion Jesus, the roles other persons played in the crucifixion, and the method of inquiry.
 Patrick J. Hurley, Logic (Belmont, CA: Thomson Wadsworth, 2008), 519.
 For an in-depth look at Bayes’ Theorem applied to arguments, particularly theistic arguments, see Richard Swinburne, The Existence of God (Oxford: Oxford University Press, 2004) 66-72.