The current question is inspired by this one: Which one is the null hypothesis? Conflict between science theory, logic and statistics?
Paul Meehl attributed the first occurrence of using a null hypothesis other than that predicted by theory to Karl Pearson. Are there earlier examples of this behavior? Also, what justifications for doing so have been put forward since?
Paul Meel wrote:
As I pointed out in my 1967 article, when the physicist uses a probable error in this second way, improvement in the quality and number of measurements leading to a lessened standard error subjects the theory to a greater risk of falsification, because here a “significant deviation” means a deviation from the predicted point value or curve type. That is how Karl Pearson’s original invention of chi square at the turn of the century worked. His idea of chi square was as an indicator of frequency discordance, asking for example, does an observed distribution depart significantly from the frequencies in class intervals as given by the Gaussian (or other theoretical) function? This I call the strong use of a significance test. But then occurs a development in the use of chi square, at Pearson’s own hands admittedly, in which the “theoretical” or “expected” values of cell frequencies, rather than being positively generated by an affirmative substantive theory generating a certain mathematical form, are instead specified by the hypothesis that two variables are not related to one another. So the expected values of cell tallies are provided by multiplying the marginals on the hypothesis of independence, using the product theorem of the probability calculus. There is, of course, nothing wrong with the mathematics of that procedure. But social scientists seem unaware of the great shift methodo-logically that takes place in that reverse-direction use of a significance test, where now the substantive theory is supported by the achievement of significance in departing from the “empty” hypothesis that two things are unrelated. In the strong use of a significance test, the more precise the experiment, the more dangerous for the theory. Whereas the social scientist’s use of chi square in a fourfold table, where H0 is that “These things are not related,” I call the weak use. Here, getting a significant result depends solely on the statistical power function, because the null hypothesis is always literally false.
Source: (1990). Appraising and amending theories: The strategy of Lakatosian defense and two principles that warrant using it. Psychological Inquiry, 1, 108-141, 173-180
The 1967 article mentioned: Meehl, Paul E. (1967). "Theory-Testing in Psychology and Physics: A Methodological Paradox". Philosophy of Science 34 (2): 103–115.
The Pearson paper: Pearson, K (1904). "On the Theory of Contingency and Its Relation to Association and Normal Correlation". Drapers' Company Research Memoirs Biometric Series 1: 1–35.