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Paul Meehl is responsible for what is probably the most apt explanation for why some areas of science have made more progress than others over the last 70 years or so. Amazingly, he pointed this out in 1967 and it had seemingly no effect on standard practices:
Because physical theories typically predict numerical values, an improvement in ex-perimental precision reduces the tolerance range and hence increases corroborability. In most psychological research, improved power of a statistical design leads to a prior probability approaching ½ of finding a significant difference in the theoretically predicted direction. Hence the corroboration yielded by "success" is very weak, and becomes weaker with increased precision. "Statistical significance" plays a logical role in psychology precisely the reverse of its role in physics. This problem is worsened by certain unhealthy tendencies prevalent among psychologists, such as a premium placed on experimental "cuteness" and a free reliance upon ad hoc explanations to avoid refuation.
Meehl, Paul E. (1967). "Theory-Testing in Psychology and Physics: A Methodological Paradox" (PDF). Philosophy of Science 34 (2): 103–115.
https://dx.doi.org/10.1086%2F288135 . Free here: http://cerco.ups-tlse.fr/pdf0609/Meehl_1967.pdf
There are many science articles posted to this site that fall foul of his critique probably because researchers are not aware of it. In short, this (putatively fatally flawed) research attempts to disprove a null hypothesis rather than a research hypothesis. Videos of some of his lectures are available online:
http://www.psych.umn.edu/meehlvideos.php
Session 7 starting at ~1hr is especially good.
(Score: 0) by Anonymous Coward on Saturday January 23 2016, @04:44AM
Sure, that will let us accept astrology, extispicy, and everything else that happens to generate data that correlates with something. Instead predict something specific with your theory and test that. This is all explained in the paper, although not with those offensive examples.
The null hypothesis is not the only alternative to your research hypothesis, there are other research hypotheses to deal with. In fact, usually no one believes the null hypothesis at all (two groups of people are sampled from the exact same distribution...). It is the flimsiest of strawmen arguments to rule out a null hypothesis and take it as evidence for the research hypothesis. It really is that simple.