The present is an introductory summary on the topic of misinformative and fraudolent statistical inferences, in the light of recent attempts to reform social sciences. The manuscript is focused is on the concept of replicability, that is the likelihood of a scientific result to be reached by two independent sources. Replication studies are often ignored and most of the scientific interest regards papers presenting theoretical novelties. As a result, replicability happens to be uncorrelated with bibliometric performances. These often reflect only the popularity of a theory, but not its validity. These topics are illustrated via two case studies of very popular theories. Statistical errors and bad practices are discussed. The consequences of the practice of omitting inconclusive results from a paper, or 'p-hacking', are discussed. Among the remedies, the practice of preregistration is presented, along with attempts to reform peer review through it. As a tool to measure the sensitivity of a scientific theory to misinformation and disinformation, multiversal theory and methods are discussed.
University of Catania, Italy - ORCID: 0000-0001-7149-5213
University of Catania, Italy - ORCID: 0000-0002-2287-7343
Chapter Title
Misinformation and disinformation in statistical methodology for social sciences: causes, consequences and remedies
Authors
Giulio Giacomo Cantone, Venera Tomaselli
Language
English
DOI
10.36253/979-12-215-0106-3.10
Peer Reviewed
Publication Year
2023
Copyright Information
© 2023 Author(s)
Content License
Metadata License
Book Title
ASA 2022 Data-Driven Decision Making
Book Subtitle
Book of short papers
Editors
Enrico di Bella, Luigi Fabbris, Corrado Lagazio
Peer Reviewed
Publication Year
2023
Copyright Information
© 2023 Author(s)
Content License
Metadata License
Publisher Name
Firenze University Press, Genova University Press
DOI
10.36253/979-12-215-0106-3
eISBN (pdf)
979-12-215-0106-3
eISBN (xml)
979-12-215-0107-0
Series Title
Proceedings e report
Series ISSN
2704-601X
Series E-ISSN
2704-5846