arbiter
JournalsAccount

If the street is wet, is it raining? The fallacy of affirming the consequent and the misuse of valid statistical evidence

Allen S. Lee

Journal of Information Technology2025https://doi.org/10.1177/02683962251365285article
AJG 4ABDC A*
Weight
0.50

Abstract

In this Debates and Perspectives article, I take the perspective in which there is past research that has misused valid statistical evidence by incorporating it into the reasoning known in formal logic as the “fallacy of affirming the consequent.” I explain what the fallacy is, provide details on how three published studies commit it, distinguish between valid statistical evidence and its misuse, and mention the logic of modus tollens as an alternative to the logic of the fallacy of affirming the consequent. I direct criticism at the research paradigm that the authors of the studies are practitioners of. A ramification for past research that has misused valid statistical evidence by incorporating it into the fallacy of affirming the consequent is that it needs to be re-examined and then reconducted using the logic of modus tollens.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1177/02683962251365285

Or copy a formatted citation

@article{allen2025,
  title        = {{If the street is wet, is it raining? The fallacy of affirming the consequent and the misuse of valid statistical evidence}},
  author       = {Allen S. Lee},
  journal      = {Journal of Information Technology},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/02683962251365285},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

If the street is wet, is it raining? The fallacy of affirming the consequent and the misuse of valid statistical evidence

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.