via Carl Zimmer, Dr. Jon Brock in his blog, “Cracking the enigma,” has some thoughts on why null hypotheses don’t suck so bad as so many people think. Null hypotheses are generally along the lines of, “there is no difference between these groups,” or “this variable has no effect on something,” or “there is no relationship between variables.” The more general statistical statement behind the null hypothesis is usually along the lines of “this phenomenon can be explained just as well by a completely random process.” I’d agree with Brock that it seems that a good many researchers (not me!) view the null hypothesis as a bore or meaningless. But I like his final thought:
This brings me neatly to my final point. In research on disorders such as autism or Williams syndrome, a significant group difference is considered to be the holy grail. In terms of getting the study published, it certainly makes life easier. But there is another way of looking at it. If you find a group difference, you’ve failed to control for whatever it is that has caused the group difference in the first place. A significant effect should really only be the beginning of the story.