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The performance of the network in the prediction of microbial counts was based on graphical plots and statistical indices (bias and accuracy factors, standard error of prediction, mean relative and mean absolute percentage residuals).
The child by child data analyses and interpretation were based on graphical plots (eg Figure 1) using Excel®.
The sampling properties based on graphical plots indicated adequate mixing for most parameters after a burn-in of approximately 5,000 and sampling for another 5,000.
Gaussian distribution was found based on graphical plots and the Kolmogorov-Smirnov test for normality; thus, parametric methods were used to analyze data and all data were presented as means and standard deviations (SD).
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Manual calls can be easily made by adjusting settings of the software using the GUI (figure 1) based on graphical plot (figure 2) inspection of the data clustering.
Unsupervised normalization methods make data transformations based on graphical trends visible in diagnostic plots.
Based on graphical residual analyses the data was assumed to be approximately normally distributed.
Comparisons based on graphical representations are made between numerical and exact solutions.
c Percent is estimated based on graphical display of data.
aPercent is estimated based on graphical display of data.
Most methods based on graphical networks aim at finding out weak points in the network.
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