Sentence examples for transformation data are from inspiring English sources

Due to much of the data not being normally distributed prior to transformation, data are shown as geometric mean (95%% confidence interval) unless otherwise stated.

Furthermore, a new additivity rule based on non-isothermal transformation data, analogous to the traditional additivity rule based on isothermal transformation data, is introduced.

Before 4D-Fourier transformation, data were zero-filled to 64 × 64 × 64 points in the spatial domain.

Control transformation data is given in absolute numbers of hygromycin resistant calluses and percentages of transgenic plants, always relative to the previous step.

If variance was not homogeneous following transformation, data were compared using Kruskal-Wallis tests (for multiple comparisons) or Mann-Whitney U-tests (for two-way comparisons) and Bonferroni p-value corrections were used to correct for nonparametric multiple comparisons.

Using different transformation methods, data are visualized by using the geospatial map, time series curves, and pixel-oriented visualizations.

Furthermore, component equations relying on nonlinear transformations of data are nonadditive.

Logarithmic transformation of data is commonly used as this transformation tends to provide values that are approximately normally distributed and for which ANOVA tests are appropriate [ 30].

Percent data of disease incidence were statistically analyzed after arcsine square root transformation; however, untransformed data are presented.

After this transformation gene expression data are presented in the units of standard deviation of the background.

Appropriate transformations of the data are difficult.