Quote:
Originally Posted by Ken G
Perhaps Tim is saying there is no error source that is really that systematic over such a wide array of methods, I can't really speak to that-- I merely point out that such would be an essential piece of that type of argument.
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That's the general idea. This thread is devoted to only one measurement, singled out for special treatment. But how does one go about the task of figuring the probability that any one particular measurement is "right"? It can only be done by comparing the one measurement to a population of like measurements. In this case, the population of measurements given by Huchra serves that purpose. Because they are all derived from different methods, they don't all share the same systematics. So the spread of measurements is a fair representation not only of random uncertainties, but systematic uncertainties.
It only needs to be shown that the given value (84) is significantly high compared to the population, to argue that it is unlikely. Note that I am only saying that it is improbable, not impossible. Just consider the inverse argument. If you are going to claim that this one measurement must be likely correct, then how do you explain all the others being unlikely? It seems unreasonable to me that they would be.