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Figure from:Sex estimation in brazilian sample: qualitative or quantitative methodology?

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Table 2. Logistic regression mode/for sex determination. Table 3 shows that the method results in 85.2% sensitivity, 76.2% specificity, and 81.1% accuracy, being, therefore, more effective in the prediction of sex than the mere random hit.

Table 2 Logistic regression mode/for sex determination. Table 3 shows that the method results in 85.2% sensitivity, 76.2% specificity, and 81.1% accuracy, being, therefore, more effective in the prediction of sex than the mere random hit.

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Table 1. Means (+ standard error) of the variables studied according to the sex. There was normal distribution (p>0.05), and variances were similar (p>0.05) for all variables. Data analysis showed balance inthe number of male and female samples (Chi-squared, p=0.24), and race did not differ between sexes. However, all measures were significan- tly (p<0.01) higher in males.
Table 1. Means (+ standard error) of the variables studied according to the sex. There was normal distribution (p>0.05), and variances were similar (p>0.05) for all variables. Data analysis showed balance inthe number of male and female samples (Chi-squared, p=0.24), and race did not differ between sexes. However, all measures were significan- tly (p<0.01) higher in males.
Table 3. Prediction of sex according to the logistic regression.
Table 3. Prediction of sex according to the logistic regression.
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