Ok, so maybe your definition does correspond to a p-value after all. It&#x27;s hard to say as you have refused to discuss concrete cases (like the fair coin or the loaded die, which are standard examples to introduce p-values). But if you&#x27;re actually calculating a p-value then it won&#x27;t behave as you expect. It won&#x27;t converge to anything (edit: if the null hypothesis holds). P-values are by definition uniformly distributed when the null hypothesis is true. If your &quot;p-value&quot; is not, then it&#x27;s not a p-value. It really is that simple. Or maybe everyone else is using the wrong &quot;p-values&quot; and yours are the real thing. You can believe it if you want.<p>Please disregard my previous questions, I see no point in continuing this discussion. But you might want to read a bit more about p-values: you won&#x27;t find anyone (I hope!) sharing your point of view. Once you understand what the p-value is, and what it is not, you might indeed conclude that they are entirely useless. Of course it&#x27;s your right to avoid learning what p-values really are, and keep the faith. It&#x27;s your choice.<p>Do you think it&#x27;s purely coincidental that this this figure <a href="https:&#x2F;&#x2F;atlas.web.cern.ch&#x2F;Atlas&#x2F;GROUPS&#x2F;PHYSICS&#x2F;CONFNOTES&#x2F;ATLAS-CONF-2012-170&#x2F;fig_03.png" rel="nofollow">https:&#x2F;&#x2F;atlas.web.cern.ch&#x2F;Atlas&#x2F;GROUPS&#x2F;PHYSICS&#x2F;CONFNOTES&#x2F;ATL...</a> includes the sigma=0 (null hypothesis) line at 0.5 and not at 1? (Hint: the expect value of the p-value under the null hypothesis is 0.5.) (That&#x27;s a rhetorical question: I already know it&#x27;s because this is not a well-formed experiment or something.)