Time, Prediction, and Postdiction

I do not make hypothesis, I am not going to say what time is. What you find here are ideas on how we assign time, the actual methods, actions, and things, that we use.

There is a debate in Philosophy and Statistics having to do with the Frequentist v.s. the Fiducial view. Bayes v.s. the Rest.

In one case we count the possibilities in front of us, and define probability. One Head, One Tail, probability $$\frac{1}{2}$$. The frequency we will find in the future is $$\frac{1}{2}$$. In the other case, we GUESS an answer, $$\frac{1}{2}$$, and then throw the coin for ever and ever, and voilà! We discover that the number of times heads come  is $$\frac{1}{2}\times N$$, where $$N$$ is the number of times we have done the experiment, and where we are willing to change our guess, as we get more and more information.

 One approach looks more into the past, and the other more into the future, thus time appears.

Since for me, time is not a river that flows independently of everything else, I do not know what TIME IS; I hereby define time as the method to know. Bayes against the rest. It is interesting that the river guy, Isaac Newton was in the Royal Society, and Bayes was not in as good standing as Newton in that Society. In my view Bayes has helped his descendants, us, more to understand time than Newton did.

Prediction or Postdiction, that is the Question.

I vote for Bayes, we do not know the future, and will never know. Nevertheless, we can always guess, and on the basis of new information make a better guess.

That is how we get time. I don't know what time is, we will know more and more as we do more experiments, like Michelson and Morley did.