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Using a strawman null hypothesis is the most fundamental problem with NHST as commonly practiced, so it probably belongs on both pages. One can read the 1904 Pearson paper (apparently the first use of a strawman) to see that he did not consider the consequences at all.
I have not been able to find any pro-NHST argument addressing Meehl's critique of this or, more generally, justifying the "disproving the opposite of your theory" use of NHST. This appears to be simply absent from the literature, the discussion is completely one-sided against doing this yet the practice continues. I doubt it can be justified, it renders the entire procedure pointless as far as I can tell. All the other confusion seems to stem from people trying to make sense of this non-productive behaviour they have been trained to perform.126.96.36.199 (talk) 17:28, 16 July 2014 (UTC)
I would like to expand on Cohen criticisms of NHST
*"[I]t does not tell us what we want to know"
What we want to know is: given our data, what is the probability of the null hypothesis being true. But what the p-vlaue tells us is: given that the null hypothesis is true, what is the probability of obtaining our data? --1980na (talk) 01:23, 1 August 2014 (UTC)
It is perfectly possible to selectively quote Cohen as a Bayesian advocate. His recommendations in the subject article do not support that. He did not recommend replacing NHST, but supplementing it with exploratory data analysis and reporting effect sizes.188.8.131.52 (talk) 01:51, 7 August 2014 (UTC)
As copied directly from the cited source here (potentially a copyright violation), the text under section /* The testing process */ reads: There should be a well-defined statistical statement (the null hypothesis (H0)) which allows to attach an attribute (rejected): it should be chosen in such a way that it allows us to conclude whether the alternative hypothesis can either be accepted or stays undecided as it was before the test. The grammatical error is the omission of the word "us" between "allows" and "to". But the larger problem is that, if I'm not mistaken, this is talking about setting the p-value, which is the probability of observing an effect given that the null hypothesis is true, but attempts to address the issue in a shorthand, that is less than clear outside of the context of the original source. --Bejnar (talk) 16:43, 12 August 2014 (UTC)
Well spotted. I removed that passage, and another from the same source, that were copied (or very closely paraphrased) from the book you linked to. They were added in this edit by an editor who stopped editing in 2010. Qwfp (talk) 17:32, 12 August 2014 (UTC)