I just stumbled on a pretty nice article highly critical of statistical tools in science or more exactly of how these are misused.
Tom Siegfried, Odds are it's wrong (at Science News).
... there’s no logical basis for using a P value from a single study to draw any conclusion. If the chance of a fluke is less than 5 percent, two possible conclusions remain: There is a real effect, or the result is an improbable fluke.
... a study with a very large sample can detect “statistical significance” for a small effect that is meaningless in practical terms.
To infer the odds that a barking dog is hungry, for instance, it is not enough to know how often the dog barks when well-fed. You also need to know how often it eats — in order to calculate the prior probability of being hungry.
A good weekend read for the statistically fed up (P<0.0001).