Death as an outcome is not personally observable. Hence, we can only estimate its nature. Simply put Bayes’ theorem (alternatively Bayes’ law or Bayes’ rule) describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
My model uses Bayes to estimate the nature of death-related outcomes as random events (an agnostic premise). This model is similar to the classic Monty Hall Problem, although it does not consider choice.
Bayesian priors for this model are as follows:
- After-life is a dichotomous event. One has equal probability of experiencing an after-life;
- States of being are polychotomous discrete events. Experiencing or not experiencing an after-life have equal probability of a positive, negative, or neutral disposition;
The model is as follows:
Application of Bayes in Estimation of Post Death States
n=n event; A=After-life event; P=probability.
This model suggests that the the three death states are equally probable. Arguably, the likelihood of a negative outcome is approximately 33%. Obviously, such a model assumes randomness, but is death a random or predetermined event? The model also begs the following questions:
- Is after-life dichotomous? Do other potential states exist?
2. Similarly, are death outcomes sufficiently explained by neutral, negative, or positive states? Are there conceivable outcomes that better encapsulate all possible states?