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In both cases, the random fluctuations obstruct focusing that occurs at source locations.
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In both cases, the truly random generation of the sequence could not be properly assessed because either the original codes are not provided or they cannot be matched to patients.
In both cases, the same similarity after random reshuffling of items is shown.
For both cases, the probability of a random occurrence was estimated using a binominal distribution: the probability of finding 2 columns of group 1 in a window of 9 columns is 2%, and the probability of finding three or more columns of either group 1 or group 2 is 2%.
In both cases the insertion was non-random and targeted a specific locus.
In both cases, the key insight is that random variation is capable of generating a more effective gradient for population dynamics.
In all cases, the random error of the Y position was less than ±0.01 mm.
In both cases, the results are averaged over 100 random selection of 200 users.
In both cases the resulting estimates are subject to random errors associated with the finite averaging time.
In both cases the lines were obtained by advancing random individual F2 plants to the F7 generation by single-seed descent.
In both cases, the resulting 'random' individual mutants (Darwinian variations) are tested by physicochemical and biological environments for short-term viability ('staying alive') and for reproductive competence leading to heredity (ancestry, lineages) on evolutionary timescales (Darwinian natural selection).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com