Abstract
There have been many criticisms of null hypothesis significance testing (NHST), including important ones made by Dr. Hung Nguyen. The goal of this chapter is to honor Dr. Nguyen for his important scientific contributions by introducing a new argument against NHST that complements the arguments he already has made. Specifically, NHST aficionados sometimes justify NHST by arguing that it is based on Popper’s falsificationist philosophy of science, which has a history of being very popular among scientists in the 20th century, and much of this popularity continues into the 21st century. In contrast, I argue that NHST is inconsistent, rather than consistent, with Popper. I further argue that there are problems with Popper’s philosophy, at least in the simple form used to justify NHST.
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Notes
- 1.
In addition, we wrote an article together that included authors from many countries [14].
- 2.
The interested reader can consult Einstein [4] for an accessible account, in Einstein’s own words.
- 3.
Some hypotheses are directional, in which case the alternative hypothesis has a 50% chance of being correct, rather than a close to 100% chance of being correct. But even 50% cannot be considered to approach anything close to what Popper would have said to be bold.
- 4.
To be fair, although auxiliary assumptions are generally brought up to criticize Popper or neo-Popperian falsificationist philosophies, Trafimow [13] showed that they are problem for verification too. That is, empirical victories can be credited to the theory or to auxiliary assumptions. The ambiguity creates problems for theory verification and not just theory falsification.
- 5.
There are more sophisticated falsificationist positions, such as that suggested by Andersson [1]. However, to my knowledge, nobody has used Andersson’s more sophisticated approach to justify NHST. In my judgment, even more sophisticated falsificationist positions are incompatible, rather than compatible, with NHST.
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Trafimow, D. (2021). The Falsificationist Foundation for Null Hypothesis Significance Testing. In: Kreinovich, V. (eds) Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas. Studies in Computational Intelligence, vol 892. Springer, Cham. https://doi.org/10.1007/978-3-030-45619-1_16
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