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Alternative statistical approaches to the use of data as evidence for hypotheses in human behavioral ecology
Author(s) -
Towner Mary C.,
Luttbeg Barney
Publication year - 2007
Publication title -
evolutionary anthropology: issues, news, and reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.401
H-Index - 85
eISSN - 1520-6505
pISSN - 1060-1538
DOI - 10.1002/evan.20134
Subject(s) - sociocultural evolution , evolutionary anthropology , ecology , human biology , status quo , field (mathematics) , empirical research , data science , empirical evidence , psychology , epistemology , sociology , computer science , biology , anthropology , political science , philosophy , mathematics , pure mathematics , law
In their ambitious Evolutionary Anthropology paper, Winterhalder and Smith1 review the history, theory, and methods of human behavioral ecology (HBE). In establishing how HBE differs from traditional approaches within sociocultural anthropology, they and others laud its hypothetical‐deductive research method.1–3 Our aim is to critically examine how human behavioral ecologists conduct their research, specifically how they analyze and interpret data as evidence for scientific hypotheses. Through computer simulations and a review of empirical studies of human sex ratios, we consider some limitations of the status quo and present alternatives that could strengthen the field. In particular, we suggest that because human behavioral ecologists often consider multiple hypotheses, they should use statistical approaches that can quantify the evidence in empirical data for competing hypotheses. Although we focus on HBE, the principles of this paper apply broadly within biological anthropology.