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Re:Not Even Scientists Can Easily Explain P-values by evanpw on Thursday November 26, 2015 @09:12AM (#10633030)
I'll give you the benefit of the doubt and assume that you aren't deliberately trolling me, but you do seem to be deeply confused. I'll just give you a link to some lecture notes that go all the way from the axioms of probability (lecture 1) to p-values (lecture 12) and leave it at that: http://www.win.tue.nl/~rmcastro/2DI90/index.php?page=lecture....
Re:Not Even Scientists Can Easily Explain P-values by jsprogrammer on Thursday November 26, 2015 @11:56AM (#10633723)
Thanks for the massive set of pages. I already went through a similar course a long time ago.

You'll note that the notes don't derive the calculation of p-value. It merely gives a trivial example (curiously, the sum of two probabilities) with a fiat interpretation.

It's curious that my last post, merely quoting the third axiom and showing its properties plain, makes you think that I am deeply confused, when you cannot even refute trivial points and must resort to arguments (poor, in that they do not address our issue here) from authority.

Re:Not Even Scientists Can Easily Explain P-values by germanier on Friday November 27, 2015 @09:29AM (#10637429)
I assume you refer to page 28 in the first slide deck? If you would have read closely you would have noticed that it says:

> We will restrict ourselves to discrete sample spaces for now, to avoid some technical difficulties…

In the later lectures they take a look at sample spaces that are uncountably infinite. Good luck working with a sum there.

Re:Not Even Scientists Can Easily Explain P-values by jsprogrammer on Friday November 27, 2015 @03:31PM (#10638724)
No. I am referring to lecture 12 (ie. Ch9).

What reformulation of the probability axioms are you using to eliminate the sum in the third axiom?

The axioms may be trivially extended to bounded intervals (a la calculus).