In an opinion piece in the Financial Post, Stephen Ziliak goes into the land of hyperbole, declaring that all significance testing is junk science. It starts like this:
I want to believe as much as the next person that particle physicists have discovered a Higgs boson, the so-called “God particle,” one with a mass of 125 gigaelectronic volts (GeV). But so far I do not buy the statistical claims being made about the discovery. Since the claims about the evidence are based on “statistical significance” – that is, on the number of standard deviations by which the observed signal departs from a null hypothesis of “no difference” – the physicists’ claims are not believable. Statistical significance is junk science, and its big piles of nonsense are spoiling the research of more than particle physicists.
He goes on to say:
Statistical significance stinks. In statistical sciences from economics to medicine, including some parts of physics and chemistry, the ubiquitous “test” for “statistical significance” cannot, and will not, prove that a Higgs boson exists, any more than it can prove the reality of God, the existence of a good pain pill, or the validity of loose monetary policy.
While I have said many times in this blog that I, too, think significance testing is mis-used, it is ridiculous to jump to the conclusion that “Statistical significance is junk science.” Ironically, Mr. Ziliak is engaging in exactly the same all-or-nothing thinking that he is criticizing.
You name any statistical method: confidence intervals, Bayesian inference, etc. and it is easy to find people mis-using it. The fact that people mis-use or misunderstand a statistical method does not render it dangerous. The blind and misinformed use of any statistical method is dangerous. Statistical ignorance is the enemy. Mr. Ziliak’s singular focus on the evils of testing seems more cultish than scientific.