Sentence examples for distribution and statistics from inspiring English sources

The patient distribution and statistics according to this algorithm are illustrated in Figure 3 and in Table 3.

For comparison, energy of gas molecules is described by Maxwell-Boltzmann distribution and statistics and in a simplified form can be expressed by: Ni/N = e-ΔE/kT, where N is the total number of particles; Ni is the number of particles with energy by ΔE higher than a certain energy (usually probabilities Ni/N are considered); Bolzmann constant k = 1.38*10−23 J/K, T is temperature (e.g. 57 p.203).

While intraspecies background mutation rates are indeed similar between community members across this well-conserved subsampling of protein-coding genes, notably, significant differences in Ks distributions and statistics were observed between phototroph- versus chemotroph-dominated communities (Fig. 3).

(D ) The peak force distributions and statistics (mean ± SEM) of stalling and releasing events in pf18 cells.

The data analysis task was done using the SPSS software application and it was carried out in two levels; namely descriptive statistics (center-oriented statistics and distribution) and analytical statistics (Spearman's Correlation Coefficient in order to test the correlational hypotheses of the research).

Outputs from the model quantified the evolving texture in terms of pole figures or crystallite orientation distribution functions and statistics on the grain structure such as the grain-size distribution and boundary-misorientation distribution function.

All data will be checked for Gaussian distribution and parametric statistics will be used were appropriate, otherwise non-parametric statistics will be applied.

Alcohol or fluid intake was not normally distributed, as shown by the Shapiro Wilk's test (W < 0.95 suggests skewed distribution) and nonparametric statistics were used.

Bubbles distribution and turbulent statistics of the liquid phase are comprehensively analyzed.

Demography, statistical study of human populations, especially with reference to size and density, distribution, and vital statistics (births, marriages, deaths, etc.).

In this paper, we propose a novel feature which learns discriminative information based on data distribution and shape statistics for pedestrian detection.