We do ten experiments. A scientist observes the results, constructs a
theory consistent with them, and uses it to predict the results of the
next ten. We do them and the results fit his predictions. A second
scientist now constructs a theory consistent with the results of all
twenty experiments.
The two theories give different predictions for the next experiment. Which do we believe? Why?
One of the commenters links to Overcoming Bias, but as of 11PM on Sep 28th, David's blog's time, no one has given the exact answer that I would have given. It's interesting that a question so basic has received so many answers.
Experience alone leads me to pick Theory #2. In what I do I'm constantly battling academic experts peddling Theory #1. Typically they have looked at say 10 epidemiological studies and concluded that the theory "A causes B" is consistent with the data and thus true. A thousand lawsuits against the maker of "A" are then launched on behalf of those who suffer from "B".
Eventually, and almost invariably with admittedly a few notable exceptions, the molecular people then come along and more convincingly theorize that "C causes A and B" such that the reason plaintiff was say ingesting "A" and then suffering from "B" was because "C" was producing an urge/need for "A" as an early symptom of the eventual "B". Or, to take a more concrete example, it may be that they demonstrate that plaintiffs were exposed to "A" (e.g. a vaccine) at the typical age of onset (e.g. autism) of "B" so that the perceived causal connection was merely coincidental.
The ability to identify and control for confounders is for some reason (perhaps to do with overcoming bias) heightened in the second set of eyes to review data and the theories they generate.
David D. Friedman asks:
One of the commenters links to Overcoming Bias, but as of 11PM on Sep 28th, David's blog's time, no one has given the exact answer that I would have given. It's interesting that a question so basic has received so many answers.