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Feb 3, 2020 at 7:13 comment added Richard Hardy @SextusEmpiricus, sounds right. Thank you.
Feb 2, 2020 at 21:14 comment added Sextus Empiricus @RichardHardy I believe the goal is to test whether the data is incompatible with $H_0$. Fisher's hypothesis testing is a search for anomalies (with regard to the theory that there are no effects).
Feb 2, 2020 at 21:08 comment added Richard Hardy ...Fisher's implicit alternative is much broader than the explicit alternative of Neyman-Pearson (NP). Under the alternative Fisher allows for the model to be misspecified in an arbitrary way, while NP remain within the specified model. It is too late for me to continue today, but I will return. +1 anyway.
Feb 2, 2020 at 21:06 comment added Richard Hardy Thanks for the update. I think I found what I was looking for, thanks to @whuber's comment and Spanos "Probability Theory and Statistical Inference" (1999), Chapter 14. The latter chapter contains what I must have meant. According to my understanding of Spanos interpretation of Fisher, there is no alternative there, while the idea of the test is to see how well the data is compatible with $H_0$. ctd...
Feb 2, 2020 at 20:57 history edited Vasilis Vasileiou CC BY-SA 4.0
I've added some info about the case of Fisher's tea test
Feb 2, 2020 at 19:52 comment added Vasilis Vasileiou Ah yes, I think you know to what you are referring to, let me edit my answer
Feb 2, 2020 at 19:29 comment added Richard Hardy Thank you for your answer! It is bridging the gap pretty nicely. However, I think Fisher did not consider an alternative hypothesis (it came later with Neyman-Pearson), yet he defined the $p$-value. Could you please comment on that?
Feb 2, 2020 at 19:01 history answered Vasilis Vasileiou CC BY-SA 4.0