Statistical methods in biology are strongly encouraged: they are quantifiable, unbiased, and usually the only ones that are accepted as evidence.
However, it doesn't seem like the whole picture.
Say, someone wants to prove the hypothesis that wings are used for flight. He (or she) conducts an experiment: takes two groups of birds, ties up wings of all birds in one of the groups, then throws them out of a window and gets statistically significant data that birds with tied wings do not fly.
However, strictly speaking, he didn't prove that birds use wings to fly: only that birds with tied up wings didn't fly when thrown out of window. Or, as they say, correlation does not imply causation.
To tie the hypothesis to the results, he might include a paragraph in the discussion that "wings have large area, there are muscles that can flap them etc" - in other words, explain how wings could be used to fly. However, this explanation isn't statistical, or quantifiable: he just wrote a "story", perhaps used some common sense - but last time I checked, it's not evidence.
And that's pretty much what happens in every paper on biology: when they try to prove some mechanism, they include an experiment results and stats for a single aspect that is related to the mechanism (which, obviously, cannot explain the mechanism on its own), but then, when it comes to discussion, they just drop all the numbers and start explaining the phenomenon "logically" and eventually come to the conclusion. To be honest, they could've done no experiment at all and just went to explanation straightaway.
So what I wanted to ask:
- Is there such a method of proof in biology as "proof by explanation", or something like that - when the author just explains the causual effects from, say, physics perspective and comes to a conclusion? Perhaps, even something similar to mathematical proof? Does this constitute valid evidence?
- Are there any formal requirements for such proof? Perhaps, some way to quantify it or reduce to a "formula" of some sort?
- Say, I wanted to publish a paper about some new protein that affects testosterone production. If I did no stats at all, or experiments like trying to remove the gene for the protein from some individuals and seeing what happens in comparison to control group, but instead just extracted and described the structure of the protein, identified the binding sites to some testosterone precursor, and explained how it can affect the testosterone production chemically, would it be a valid paper?