Sentence examples for parametric deviations from inspiring English sources

To create industry awareness, we demonstrate two examples out of an OEM driven study on mechanical induced parametric deviations which relate to corresponding product verification/validation issues that can end up in real, but which are mostly classified as no fault found (NFF) issues.

Analog circuit fault diagnosis is challenging due to the parametric deviation and the difficulty in signal quantizing.

Appropriate parametric (for normally distributed data) and non-parametric (deviation from normality in data distribution) approaches will be used to ascertain clinically meaningful group differences at each time point.

This non-parametric statistic is approximately equivalent to the parametric standard deviation, and can be used to show areas where there is greater or less variation between GCMs.

Distributions were checked and as all variables approximated normality with relatively small deviations, parametric tests were used.

For continuous data (e.g. age), means and standard deviations (parametric data) or medians and percentiles (nonparametric data) will be calculated.

Continuous data are reported as medians and percentiles (nonparametric data) or as means and standard deviation (parametric data), and categorical data as numbers with percentages.

Categorical variables were expressed as percentages; continuous variables were expressed as means ± standard deviation (parametric variables) or median and interquartile range (IQR) (nonparametric variables).

Descriptive results of continuous data were expressed as means with standard deviations for parametric data or as medians with ranges for non-parametric data.

For continuous variables, we used means and standard deviations for parametric data and reported median and range for non-parametric data.

It is shown that the observer is robust against bounded model deviations (both parametric and nonmodeled dynamics).