Humots,
- I think that the following statement shows that I don't need to say anything about the theory being true...
From
http://plato.stanford.edu/entries/bayes-theorem/:
1. Conditional Probabilities and Bayes' Theorem
The probability of a hypothesis H conditional on a given body of data E is the ratio of the unconditional probability of the conjunction of the hypothesis with the data to the unconditional probability of the data alone.
Note: this is simply a statement of the definition of conditional probability:
P(H|Data) = P(H and Data) / P(Data)
I think you may be confusing two different uses of the word "hypothesis".
Hypothesis: John Doe died in 2000
Hypothesis: a = G M / R^2
The first hypothesis is about an event.
The second hypothesis is a scientific model.
I don't believe that probability can be applied to both hypotheses in the same way, but I may be wrong. My knowledge of Bayes' Theorem is mostly about the math, not about its applications.
Consider the following statement (
Higgs boson confirmed):
"Physicists announced on July 4, 2012, that, with more than 99 percent certainty, they had found a new elementary particle weighing about 126 times the mass of the proton that was likely the long-sought Higgs boson."
Does this mean that
- the Standard Model has a 99 percent certainty of being valid, or
- evidence that supports the Standard Model has a 99 percent chance of being right?