gears, cogs, machine

Mechanistic, repetitive, and unreflective hypothesis testing

Mind your Ps and Qs – use your IQ…

Statistics has been called “the grammar of science” (Cumming, 2012) and inferential reasoning processes lie at the very heart of conclusions drawn from scientific research. Currently, Fisherian null hypothesis significance testing (hereafter NHST) is the dominant inferential method in many scientific disciplines (Fisher himself was a geneticist). Unfortunately, it is a robust empirical finding that the underlying Aristotelian syllogistic logic of NHST is widely misunderstood, not just by students, but also by their teachers (e.g., Haller & Krauss, 2002), by professional academic researchers (e.g., Rozeboom, 1960), and even by professional statisticians (e.g., Lecoutre, et al., 2003). That is, unsound logical thinking and wrong knowledge and beliefs concerning NHST are ubiquitous in the scientific community. Peer-reviewed scientific publications, textbooks, lecturers, and high-ranking professionals perpetuate the misinterpretations of NHST (they hand down mutated memes). In order to break this vicious circle, researchers should (1) acknowledge the problem, (2) understand the logical pitfalls, and (3) learn about alternative inferential techniques (i.e., Bayesian probability theory).


Further References

Gigerenzer, G.. (2004). Mindless statistics. Journal of Socio-Economics

Plain numerical DOI: 10.1016/j.socec.2004.09.033
DOI URL
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Haller, H., Krauss, S., & Kraus, S.. (2002). Misinterpretations of Significance : A Problem Students Share with Their Teachers ?. Methods of Psychological Research

Plain numerical DOI: www.mpr-online.de
DOI URL
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Cohen, J.. (1994). The earth is round (p < .05). American Psychologist

Plain numerical DOI: 10.1037/0003-066X.49.12.997
DOI URL
directSciHub download

Cohen, J.. (1995). The Earth Is Round (p < .05): Rejoinder. American Psychologist

Plain numerical DOI: 10.1037/0003-066X.50.12.1103
DOI URL
directSciHub download

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