The t-test was used to characterize the statistical significance when comparing different means; the significance level was set at P = 0.05.
The large prospective studies looking at glucose management in the critically ill have compared different mean blood glucose targets, with little or less attention paid to other glucose metrics, such as glycemic variability [ 1, 4, 6, 7].
We adopted two measures to compare different genotypes by means of a Pearson correlation metrics: i) auto-correlation: Pearson r between 0 h (t0) and other time points (t1, t4) of the same genotype and ii) cross-correlation: Pearson r between wildtype and other genotypes at same time point (Methods).
In the case of more than two groups (e.g. when comparing different country means) differences were tested by using analysis of variance models (ANOVA).
Here we only intend to use estimated PSFs as a means to compare different algorithms.
However, because of the linear correlation shown in Figure 2 between the total CO2 produced and the mass of consumed cellulose, it is reasonable to assume that CO2 profiles provide a means to compare different substrates.
Although it is not directly related to benchmarking (as there is no standard procedure meant to compare different systems/components concerning robustness), authors usually refer to robustness testing as robustness benchmarking.
In order to compare nMT different means of transport (e.g. a mid-size class passenger car and a city bus) in reference to one specific performance criterion (e.g. the averaged fuel consumption per passenger), a developed traffic performance index TPI i is introduced, see Eq. 4: {TPI}_i=10min left(frac{V_t}{V_{M_i}},1right),kern0.5em i=1,2dots {n}_{mathrm{MT}} (4).
When comparing different working positions, mean scores among physicians, nurses, chief nurses, clinical supports and other positions were significantly different in all safety factors but not in Stress recognition.
As such, structural listening often means comparing different moments from within a particular piece.
