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The number of trees required to be sampled to give 95%% confidence at 1 and 5 % prevalence was determined using the sample formula by Kean et al. (2015).
Instead of viewing most as a second-order predicate, we can specify its semantics by analogy with classical quantifiers: The sample formula is true (under a given interpretation) just in case a majority of individuals satisfying dog(x) (when used as value of x) also satisfy friendly(x).
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Although Behrsin et al. provide a number of different sample formulas for deriving codon mutation frequencies given nucleotide frequencies, we describe a generalized method of deriving these frequencies for two reasons.
But without the hospitals' free, routine disbursement of samples, formula will no longer have the appearance of being normative, nor of being as wholesome as mother's milk.
Furthermore, we evaluate the large-sample formula for ICC estimates and standard errors using the bootstrap method.
In [19], Qian has introduced the following regularized sampling formula.
The second formula to be considered is the approximate sampling formula (ASF) treated in Weiss [83], Brown [11, 12] and Butzer-Splettstößer [22]; see also [84, pp. 64 66].
We study some problems related to the effect of bounded, additive sample noise in the bandlimited interpolation given by the Whittaker Shannon Kotelnikov (WSK) sampling formula.
The sampling formula for this model was presented by [12].
In R = (E t a r g e t ) Δ Ct t a r g e t (control-sample ) / (E r e f ) Δ Ct r e f (control-sample ) formula, E target and E ref reflect PCR efficiencies of the primers for target genes and reference genes, respectively.
The cattle and goats were selected randomly for milk sampling using multistage random sampling formula as described above.
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