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Sex and Gender Comparisons

Does Null Hypothesis Testing Create a False Dichotomy

Bibliographic Data

ID12260417
AuthorsOlga Eizner Favreau (Université de Montréal, corresponding author)
Year1997
Volume7
Issue1
Pages63-81
Publication date1997-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFeminism & Psychology (JOURNAL)
Journal identifiersISSN: 0959-3535 • E-ISSN: 1461-7161
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/0959353597071010
OpenAlexW2032125456
LanguageEN
Citations received7
References cited60

In an ongoing debate about the value of doing tests for sex differences, those in favour claim that if sex differences exist, it is important to know about them. However, the null hypothesis (NH) tests that are used for inferring group differences can detect only mean differences and provide no information about how the differences are distributed across groups. Theoretical and empirical examples show how NH rejection can occur when only a small proportion of individuals differ from all others, demonstrating that these tests are incapable of supporting inferences to general group differences. This forces a reevaluation of sex difference research which has been interpreted as distinguishing males from females in general, particularly where inferences have been to general biological factors. However, even knowing the limitations of these tests may not lead to more judicious interpretations in the context of an androcentric culture which dichotomizes the sexes

Alternative hypothesis · Biology · Context (archaeology · Econometrics · Null (SQL · Null hypothesis · Statistical hypothesis testing · Statistics · Value (mathematics · Evolutionary Psychology and Human Behavior · Mathematics · Psychology · Race, Genetics, and Society · Social and Intergroup Psychology · Social Psychology

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Unique citing works7
Citations per year0,26
Citation span1999 - 2015 (17)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 7
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