NaClhv

Theology, philosophy, science, math, and random other things
                                                                                                                                                                                                                                                                  

Bayesian evaluation for the likelihood of Christ's resurrection (Easter 2019)

This was the state of the "Bayesian evaluation for the likelihood of Christ's resurrection" post, as of Easter 2019, in the "third draft" form. Some of the formatting has been lost in the blog migration, particularly in the Jupyter notebooks, but the content has been retained. This post will remain unchanged, while the other post […]

Bayesian evaluation for the likelihood of Christ's resurrection (frozen copy)

This was the state of the "Bayesian evaluation for the likelihood of Christ's resurrection" post, as of Easter 2018, in the "second draft" form. Some of the formatting has been lost in the blog migration, particularly in the Jupyter notebooks, but the content has been retained. This post will remain unchanged, while the other post […]

Bayesian evaluation for the likelihood of Christ's resurrection

This is still a work in progress. It will change as I continue to add and edit the content. I consider this to be in its "third draft" form. It will take some more time to complete, and it may be messy in the meantime. A version of this post as it appeared on Easter […]

Bayesian evaluation for the likelihood of Christ's resurrection (Part 50)

We will consider some more miracles from other religions, but the conclusions here are not difficult to reach. A full-blown analysis is not necessary, as none of them reach anywhere near the level of evidence in Jesus's resurrection. We can just draw parallels to our previous analysis. So, for example, there's a story of Ichadon, […]

Bayesian evaluation for the likelihood of Christ's resurrection (Part 49)

Let us now consider some miraculous stories from the works of Josephus. Josephus was a Jewish historian who was active in the latter half of the first century. His works include The Jewish War and Antiquities of the Jews. They deal with the contemporary and the ancient history of the Jews, from the perspective of the […]

Bayesian evaluation for the likelihood of Christ's resurrection (Part 48)

The following are the accounts of the healing miracles of the Roman emperor Vespasian. Vespasian himself healed two persons, one having a withered hand, the other being blind, who had come to him because of a vision seen in dreams; he cured the one by stepping on his hand and the other by spitting upon […]

Bayesian evaluation for the likelihood of Christ's resurrection (Part 47)

A common argument from skeptics is that we cannot accept the miraculous stories about Jesus while simultaneously rejecting them for all non-Christian miracle-workers in world history. But that is nonsense. Of course we can discriminate between these stories. It just comes down to discerning which ones have enough evidence. So, for instance, we've already shown […]

Bayesian evaluation for the likelihood of Christ's resurrection (Part 40)

In the previous post, we demonstrated that the likelihood for Christ's resurrection came down to the number of "outliers" we can find in world history - where "outliers" are the other, non-Christian "resurrection" reports with at least a "some people say..." level of evidence behind them. The more such low-evidence cases we find, the more […]

Bayesian evaluation for the likelihood of Christ's resurrection (Part 39)

This is a jupyter notebook. It contains the python code which generates the relationship between the number of "outliers" (as previously defined) and the probability of naturalistically generating a Jesus-level resurrection report. resurrection_calculation First, we import some modules: In [1]: %matplotlib inline import numpy as np import pandas as pd from scipy.stats import genpareto Next, we […]

Bayesian evaluation for the likelihood of Christ's resurrection (Part 38)

So then, here is the summary of the basic idea: We assume that the "skeptic's distribution" will take the form of a generalized Pareto distribution. We will determine the shape parameter of the distribution by looking at how many "outliers" it has. A person's resurrection report is considered an "outlier" if it has at least 20% […]
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