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Cephalic index viewed from above the head. The cephalic index or cranial index is a number obtained by taking the maximum width (biparietal diameter or BPD, side to side) of the head of an organism, multiplying it by 100 and then dividing it by their maximum length (occipitofrontal diameter or OFD, front to back). The index was once used to ...
The mean and the standard deviation of a set of data are descriptive statistics usually reported together. In a certain sense, the standard deviation is a "natural" measure of statistical dispersion if the center of the data is measured about the mean. This is because the standard deviation from the mean is smaller than from any other point.
Swedish professor of anatomy Anders Retzius (1796–1860) first used the cephalic index in physical anthropology to classify ancient human remains found in Europe. He classified brains into three main categories, "dolichocephalic" (from the Ancient Greek kephalê, head, and dolikhos, long and thin), "brachycephalic" (short and broad) and "mesocephalic" (intermediate length and width).
Cephalometric analysis depends on cephalometric radiography to study relationships between bony and soft tissue landmarks and can be used to diagnose facial growth abnormalities prior to treatment, in the middle of treatment to evaluate progress, or at the conclusion of treatment to ascertain that the goals of treatment have been met. [5]
The cephalic index of a vertebrate is the ratio between the width (side to side) and length (front to back) of its cranium (skull). This ratio does not concern the muzzle or face, and thus is distinct from the craniofacial ratio , which compares the size of the cranium to the length of the muzzle.
Bias in standard deviation for autocorrelated data. The figure shows the ratio of the estimated standard deviation to its known value (which can be calculated analytically for this digital filter), for several settings of α as a function of sample size n. Changing α alters the variance reduction ratio of the filter, which is known to be
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The standard deviation is the square root of the variance. When individual determinations of an age are not of equal significance, it is better to use a weighted mean to obtain an "average" age, as follows: x ¯ ∗ = ∑ i = 1 N w i x i ∑ i = 1 N w i . {\displaystyle {\overline {x}}^{*}={\frac {\sum _{i=1}^{N}w_{i}x_{i}}{\sum _{i=1}^{N}w_{i}}}.}