Dedicated to the systematic debunking of Christianity, from modern Christian activities and evangelism to the problematic and contradicting Bible, via rationalism and evidence-based counterarguments.
John W. Loftus
David Madison
That is, the probability of a story being fabricated is not just the probability that scribe X would have fabricated it, but that any scribe who was in position to inject the story would have done so.
And we know that happened.
Bible interpolations are words, phrases, or whole passages added to the biblical text by copyists or editors long after the original writing. Key examples include the [16:9-20] ending of Mark, the [7:53–8:11] story of the woman caught in adultery, and the [5:7-8] Trinitarian formula in 1 John.
Third Case to Consider) The Video by Brian Blais and YouTuber Paulogia. Dr. Blais is a Professor in the Department of Biological and Biomedical Sciences at Bryant University.
I like Dr. Blais, I cited from this cite in the rent past here already.
Bad Apologetics on Bayes - Part 1
Dr. Blais has a series of of articles up on his blog, on the very subject in that video.
They did an excellent video titled, “What Bayes’ Theorem Really Says About the Resurrection” (August 2025).[9]
They did. I subscribe to Paulogia's YouTube channel. His long term partner, Shannon Q, is not too shabby at taking apologist arguments apart too.
I've followed both since they first appeared on The Atheist Experience, many years ago.
When apologist Than Christopoulos accused YouTuber Paulogia of “mathematical malpractice” for his skepticism, Paulogia enlisted physicist and statistical inference expert Brian Blais.
I seen it when it first dropped, but thanks for the reminder. I watched it again.
This video features Dr. Blais’s detailed breakdown of the debate, where he corrects the Bayesian equations, reframes the data, and argues that the apologist’s own math reveals a conclusion baked in from the start, turning a theological debate into a fascinating lesson on logic and probability. The “Maximal Data Case” for the resurrection of Jesus by Christopoulos is shown to be a sophisticated argument “for the Bible tells me so.”
I've been saying, the tool isn't broken, it's the misuse that is the problem. Dr. Blais does an excellent job in demonstrating where and why.
This video is how to use Bayes’ Theorem correctly.
Indeed. Dr. Blais aligns up with Dr. Carrier's take.
Both scholars agree that historical arguments are inherently probabilistic. They believe that Bayes' Theorem provides the most objective logical framework for evaluating past events.
Dr. Blais shares Carrier's secular perspective. He has used Bayesian analysis to critique Christian apologists for manipulating probabilities to defend the resurrection.
They both argue that traditional historical "criteria of authenticity" are highly flawed and must be replaced by structured probability.
Dr. Blais refined Carriers formula and put it through the Python computer program.
Reproducing Richard Carrier's Calculations
Where they part on this, is Carriers use of the Rank Raglan scale.
The Prior Probability of Jesus Mythicism Re-Evaluated in Light of the Gospels’ Dramatic Date
The second flaw in Licona’s argument is that although he says that the resurrection hypothesis is the best explanation, he really only means that it is the best of the explanations he considers in his book. He only considers five others. These five hypotheses obviously don’t take up 100% of the probability space. If one hypothesis is the best among a set of hypotheses that only make up a portion of the total probability space, it does not follow that it is the best explanation. There could still be explanations that Licona hasn’t considered that are better than the Resurrection.
And what Licona might count as one candidate explanation could in fact be many.
Take the case where the resurrection scriptures were edited by some unknown scribe. Then we wouldn't just have to consider the probability that one particular scribe made up a story - we would have to consider the probability that any one of some potentially large number of scribes could have made up a story.
That is, the probability of a story being fabricated is not just the probability that scribe X would have fabricated it, but that any scribe who was in position to inject the story would have done so.
In forensics this is called the chain of evidence. The more people who handle an item of evidence from a crime scene, the weaker the evidence becomes, because now there are more people who could have tampered with it.
We know very little about the chain of evidence for bible stories - there is no "chain of evidence" in the modern sense. The earliest surviving complete manuscripts date from hundreds of years later.
And the surviving manuscripts could suffer from survivorship bias, as early Christians were involved in cult warfare. The winning cult went around burning the documents of the losing cults.