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太原地区现代人头骨的研究
引用本文:王令红,孙凤喈.太原地区现代人头骨的研究[J].人类学学报,1988(3).
作者姓名:王令红  孙凤喈
作者单位:中国科学院古脊椎动物与古人类研究所 (王令红),山西医学院解剖教研室I(孙凤喈)
摘    要:本文报告了太原地区男、女组现代人头骨测量性状的基本统计量和非测量性状的出现情况,记述和讨论了它们的两侧差异和性别差异情况,建立了以多个项目测量值鉴定华北人头骨性别的判别函数。

关 键 词:人类头骨  测量性状  非测量性状  判别分析

A STUDY ON THE SKULLS FROM TAIYUAN, SHANXI
Wang Linghong.A STUDY ON THE SKULLS FROM TAIYUAN, SHANXI[J].Acta Anthropologica Sinica,1988(3).
Authors:Wang Linghong
Abstract:The basic statistics of 109 metrical traits and the incidences of 63 non-metrical traits in both male and female skulls from Taiyuan, Shanxi are reported in the present paper. The incidences of these non-metrical traits may be of use for a further comparative study. The side differences and the sexual differences of these metrical traits have been revealed by the t-tests. On the average, the orbital breadth, the height of mandibular body at foramen mentale and the breadth of mandibular notch on right side are significantly or very significantly larger than the corresponding measurements on left side in both male and female group. In male group alone, the orbital height on right is larger and the height of caput mandibular on right is smaller than on left. These side differences probably are related with the right dominence in mastication. The sexual differences in Taiyuan series are generally reflected in a larger size of male skulls. Besides, the averages of the subtense mf-mf, the naso-malar angle and the profile angle of frontal bone in male group are statistically very significantly smaller than the corresponding values in female. Using 8 metrical traits in skulls with man-dibles, the discriminant analysis leads to 92.5% cases of sexual diagnoses in accordance with those based on the morphology of postcranial bones. The discriminant analyses using a few traits in skulls without mandibles or in mandibles alone as their items produce approximately 90% accuracy. These discriminant functions have been formulated, which can be applied in the range of modern Northern Chinese skulls.
Keywords:Human skulls  Metrical traits  Non-metrical traits  Discriminant an-alyses
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