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A chi-square test examining the difference between observed species abundance digit distribution and the expected Benford distribution shows that the BCI data follow the significant-digit pattern (χ2 = 3.22, df = 8, p = 0.920).
Homogeneity of terminal digit distribution indicates a correct application of standard methodologies for risk factors measurements.
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Again, the terminal digit distributions could reasonably have occurred by chance, given a discrete uniform distribution.
We assessed first-digit distribution in estimates of weekly texts sent and cordless phone calls made.
Studies referring to empirical data concentrated solely on the leading digits' distributions, nearly always on the most significant digit only, neither discussing the relationship between the leading digits' distributions and the variable's distribution nor presenting the latter one.
The exponential distribution produces first- and second-place digits' distributions coming close to the Newcomb-Benford distribution.
Thus, the variable's distribution looks like a survival distribution whose leading digits' distributions follow the NBL, at least approximately.
Analyzed were the distributions of the following five variables plus their first- and second-place digits' distributions.
Presumably the present study is therefore the first one focusing on the connection between the variables' distribution and the leading digits' distributions, in both theoretical and empirical settings.
The closer the shape of the distribution of a random variable comes to that of a survival distribution or a distribution behaving like a survival distribution, the better follows the first- and second-place digits' distributions the NBL.
It is somewhat surprising that in the literature on the NBL the connection between the distribution of a random variable and the leading digits' distributions was investigated up to now only for a handful of mainly survival distributions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com