I am taking a graduate-level stat course so I have had reasons for reviewing basic statistical concepts. In doing so, I now believe I can perhaps shed some light on the concept of the null hypothesis and some misunderstanding evident in posts in this forum.

1) First off-- the word "null" in null hypothesis has NOTHING to do with a null in audible differences. Lots of people are confused about this--including some people who are posting the results of blind testing. The null in the hypothesis refers to an assumed "no difference" in the mean of a sample (the test data) and the population from which the sample is taken (all humans that can hear in this case). The null assumption is necessary in order to make a judgment about the probability that your test results are due to chance.

2) The null hypothesis of an experiment is choosen as something you TRY to prove false. For this reason it is often chosen to be something that would be easy to show as false, but might be much harder to be shown as true in all cases. For example, if our null hypothesis is that "nobody can hear differences between two specific cables" we can easily find this to be false by finding ONLY ONE person who can. If the hypothesis were "some people can hear differences" it would be difficult to show this to be false as no matter how many people we test that hear no differences, we can suspect that someone else, not tested, can. Why do scientists always try to something is false rather than true? Well, demonstrating that something is false is usually easier as we only have to find one case were the the contention is false. The key point of this is that the way the null hypothesis is stated HAS NOTHING TO DO WITH WHAT THE EXPERIMENTER EXPECTS OR "WANTS" TO FIND IN THE EXPERIMENT. The conventions of stating the null in a particluar way relate to practical matters of logic.

Certain wire gurus (complete with Web sites), are demonstrating not only their lack of knowledge about valid testing, but also their muddle-headed thinking abilities, when they claim things like "you can't prove a null" or "scientists are trying to find a null in cable audibility" and so on. Rest assured the scientific and mathematical communities would be more than happy to point out how or why a peer-reviewed study is making mistakes in logic, theory, or experimental practice. Scientific reaseach studies are open to all kinds of criticism and carry much much more logical weight than all the 'theories" and "white papers" written by crackpots without scientific rigor.