1. New information may affect the probability of an existing hypothesis (H).
2. An old event may be new info if it hasn’t already been considered in the current probability of H.
3. If an event is unlikely – given a particular hypothesis (H) – but the event occurs, the occurrence will tend to have a negative effect upon the probability of H — but, it need not.
4. It could be that given the complementary hypothesis – the event would be even more unlikely.
5. Or, it could be that all possible events – given H – are equally unlikely (e.g. a fair lottery) -- if so, the particular event needs to be "set apart" in a way that is relevant to the hypothesis in order to impact the hypothesis.
6. If – given H – an event is impossible, but does occur, H must be wrong.
7. Otherwise, what we call Bayesian statistics is used to evaluate the effect of a new and relevant event upon the probability of H.
8. I claim that by using my own current existence as the new info, Bayesian Statistics, virtually proves that we humans are not mortal.