Sentence examples for mean square variation from inspiring English sources

Black vertical bars indicate the RMS (root mean square) variation around a monthly average.

In Table 4, the statistical significance of the ratio of mean square variation due to regression and mean square residual error was tested using ANOVA.

The statistical significance of the ratio of mean square variation due to regression and mean square residual error was tested using ANOVA.

The statistical significance of the ratio of the mean square variation due to the regression and mean square residual error is tested using analysis of variance (ANOVA).

The statistical significance of the ratio of the mean square variation due to the regression and mean square residual error was also tested using analysis of variance (ANOVA) as shown in Table 8.

Apart from the geometry, the main difference of this sample compared to the device presented in Ref. [27] is the higher root mean square variation of the height (r h) on the island.

This loss in signal is due largely to the range limit of remote axial scanning using SSTF, which was predicted in previous theoretical work [ 13], as well as variation in coupling efficiency into the single-mode fiber, measured to have a root-mean-square variation of about 10% over this voltage range.

Other voltage events, such as short duration root-mean-square variations can also be detected using the method proposed.

Short-term precision for repeated measures was explored using intraclass correlational coefficient (ICC), mean coefficient of variation (CV%), root mean square coefficient of variation (RMSCV%) and least significant change (LSC%95).

We assessed short-term precision of repeated measures with repositioning using intraclass correlational coefficient (ICC), mean coefficient of variation (CV%), root mean square coefficient of variation (RMSCV%) and least significant change (LSC%95) [ 51].

As with the single fracture reservoir, the fraction of reservoirs that benefit from aperture variations decreases with increasing mean square of aperture variations.