“If you report results selectively, it becomes easy to prejudge hypotheses: yes, the data may accord amazingly well with a hypothesis H, but such a method is practically guaranteed to issue so good a fit even if H is false and not warranted by the evidence. If it is predetermined that a way will be found to either obtain or interpret data as evidence for H, then data are not being taken seriously in appraising H. H is essentially immune to having its flaws uncovered by the data. H might be said to have “passed” the test, but it is a test that lacks stringency or severity. Everyone understands that this is bad evidence, or no test at all. I call this the severity requirement.”