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Neyman & Pearson considered a different problem to Fisher (which they called "hypothesis testing"). They initially considered two simple hypotheses (both with frequency distributions). They calculated two probabilities and typically selected the hypothesis associated with the higher probability (the hypothesis more likely to have generated the sample). Their method always selected a hypothesis. It also allowed the calculation of both types of error probabilities.
The development of statistical hypothesis testing was shaped by a long-standing philosophical dispute between [[Ronald Fisher]] and [[Jerzy Neyman]] with [[Egon Pearson]]. Neyman and Pearson introduced a formal decision-theoretic framework in their 1933 paper, culminating in the [[Neyman–Pearson lemma]], which defines the most powerful test for a given significance level α when comparing two simple hypotheses.<ref name="NeymanPearson1933">{{cite journal|last1=Neyman|first1=Jerzy|last2=Pearson|first2=Egon S.|year=1933|title=On the Problem of the Most Efficient Tests of Statistical Hypotheses|journal=Philosophical Transactions of the Royal Society A|volume=231|pages=289–337}}</ref><ref name="NPlemma">{{cite web|title=Neyman–Pearson lemma|url=https://en.wikipedia.org/wiki/Neyman%E2%80%93Pearson_lemma|website=Wikipedia}}</ref>
Fisher, in contrast, advocated for significance testing as a method of inductive inference. He emphasized the use of the [[p-value]] as a continuous measure of evidence against the null hypothesis, without rigid accept/reject rules. In his 1958 essay *The Nature of Probability*, Fisher criticized the Neyman–Pearson approach as overly mechanical and ill-suited for scientific research, where assumptions often evolve during experimentation.<ref name="Fisher1958">{{cite journal|last=Fisher|first=R. A.|year=1958|title=The Nature of Probability|journal=Centennial Review|volume=2|pages=261–274|url=http://www.york.ac.uk/depts/maths/histstat/fisher272.pdf}}</ref>
The dispute between Fisher and Neyman–Pearson was waged on philosophical grounds, characterized by a philosopher as a dispute over the proper role of models in statistical inference.<ref name="Lenhard">{{cite journal|last=Lenhard|first=Johannes|year=2006|title=Models and Statistical Inference: The Controversy between Fisher and Neyman–Pearson|journal=Br. J. Philos. Sci.|volume=57|pages=69–91|doi=10.1093/bjps/axi152|s2cid=14136146}}</ref>▼
Fisher argued that pre-specified models and binary decisions could mislead researchers, stating:
> “We are quite in danger of sending highly trained and highly intelligent young men out into the world with tables of erroneous numbers under their arms, and with a dense fog in the place where their brains ought to be.”<ref name="Fisher1958" />
▲The dispute
In 1938, Neyman moved to the [[University of California, Berkeley]], ending his collaboration with Pearson and geographically distancing himself from Fisher. [[World War II]] interrupted the debate, which remained unresolved until Fisher’s death in 1962. Neyman later published a respectful eulogy in *Science*, acknowledging Fisher’s contributions despite their differences.<ref>{{cite journal|last=Neyman|first=Jerzy|year=1967|title=R. A. Fisher (1890–1962): An Appreciation|journal=Science|volume=156|issue=3781|pages=1456–1460|doi=10.1126/science.156.3781.1456|pmid=17741062}}</ref>
Interestingly, Neyman’s later publications included p-values and significance levels, blurring the lines between the two schools of thought.<ref>{{cite journal|last1=Losavich|first1=J. L.|last2=Neyman|first2=J.|last3=Scott|first3=E. L.|last4=Wells|first4=M. A.|year=1971|title=Hypothetical explanations of the negative apparent effects of cloud seeding in the Whitetop Experiment|journal=PNAS|volume=68|issue=11|pages=2643–2646|doi=10.1073/pnas.68.11.2643}}</ref>
==={{anchor|NHST}}Null hypothesis significance testing (NHST)===
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