Scientists are fond of placing great value on what they call skepticism: Not taking things on faith. Science versus religion, is the point. In practice this means wondering about the evidence behind this or that statement, rather than believing it because an authority figure said it. A better term for this attitude would be: Value data.

A vast number of scientists have managed to convince themselves that skepticism means, or at least includes, the opposite of value data. They tell themselves that they are being “skeptical” — properly, of course — when they ignore data. They ignore it in all sorts of familiar ways. They claim “correlation does not equal causation” — and act as if the correlation is meaningless. They claim that “the plural of anecdote is not data” — apparently believing that observations not collected as part of a study are worthless. Those are the low-rent expressions of this attitude. The high-rent version is when a high-level commission delegated to decide some question ignores data that does not come from a placebo-controlled double-blind study, or something similar. These methodological beliefs — that data above a certain threshold of rigor are valuable but data below that threshold are worthless — are based on no evidence; and the complexities and diversity of research imply it is highly unlikely that such a binary weighting is optimal. Human nature is hard to avoid, huh? Organized religions exist because they express certain aspects of human nature, including certain things we want (such as certainty); and scientists, being human, have a hard time not expressing the same desires in other ways. The scientists who condemn and ignore this or that bit of data desire a methodological certainty, a black-and-whiteness, a right-and-wrongness, that doesn’t exist.

How to be wrong.