Mathematical models can improve the accuracy of identifying sex from ancient skulls
In short: Researchers testing different statistical methods on human skulls found that a specific type of logistic regression model significantly improved sex estimation. By analyzing visual traits like the brow area and mastoid process, the study achieved 88% accuracy on modern samples and 78% accuracy on an ancient Native American group.
The study evaluated several mathematical models, including logistic regression, using cranial features from modern and ancient populations. While the models performed well, the researchers noted that because sexual dimorphism varies between groups, these specific formulas might not be reliable when applied to populations different from those used to create them.
Why it matters: Statistical models can help archaeologists identify sex from skeletal remains, but they must be used carefully across different populations.
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Sources
- Summary by Intellect · source: Research: Walker (2008). Sexing skulls using discriminant function analysis of visually assessed traits. American Journal of Physical Anthropology.
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