Sentence examples for model explains more from inspiring English sources

The model explains more wave-related variability in surface stress than previous models.

Study results show that our model explains more interactivity and uncertainty of traffic among links when compared with the traditional model of Wardrop's.

Digital competence and personal innovativeness explained 54% of the total variances in attitude to digital informal learning, while our research model explains more than 50% of total variance endogenous dependent latent variable indicate a good explanatory power (Chin, 1998).

The linear model explains more than 87% of the variance of the experimental Log K (R = 0.93 and s = 0.102 × 10−4 M−1) and leave-one-out press statistics evidenced its predictive ability (q2 = 0.82 and scv = 0.108 × 10−4 M−10−4

The adjusted R squared is 0.54, with an F statistic of 21.33 (p < 0.0001), indicating that the model explains more than half of the variation of the cost of printed media across countries.

Although it is possible to explain a large proportion of the variability in personal exposure for compounds found primarily in the home (e.g., p-dichlorobenzene, d-limonene), neither residential measurements nor our time-weighted model explains more than half the observed variability in exposure to compounds with both indoor and outdoor sources (e.g., benzene).

The model explained more than 99% of the total variance, calculated without considering the initialized point at breast height.

A quadratic model explained more of the variance (R2=0.58 0.61) than a linear model (R2=0.37 0.52) between metabolic power and individual leg mechanical power during step-to-step transitions across all velocities.

The model explained more than half of the variance in the performance of IT innovators and offered several explanations for why some firms succeeded in implementing IT service innovations while others did not.

A quadratic model explained more of the variance (R2=0.57 0.76) than a linear model (R2=0.52 0.59) between metabolic power and individual leg mechanical power during step-to-step transitions at each velocity for all slopes, and explained more of the variance (R2=0.12 0.54) than a linear model (R2=0.07 0.49) at each slope for all velocities.

Addition of stoichiometric measures and other soil attributes (e.g. soil C N, C P, δ15N) in a multiple regression model explained more of the variation than a single factor plus the land use effect (though soil order still explained a small, but significant amount of variance for measures of microbial biomass).