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On the schema-item level, this variance is even more apparent (range.08 to.81; M = .43, SE = .03).03
For the results obtained with (50~%), the variance is even smaller, as shown in Fig. 6e and f.
In rural areas, just over half of the population has access to clean water compared to more than two-thirds of those in urban communities, while for sanitation the variance is even more marked at 32.2 per cent in rural areas compared to 67.8 per cent in urban.
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For RILs, the explained variance was even lower and non-significant.
The contribution of cross-patient variance to the total variance was even smaller for SUVmax and volume at 15.5 and 13.3 %, respectively.
The ratios MSEDCT/MSElb for larger noise variances are even smaller than for σ2 = 65.
A comparison of variances was even more marked, with the variance of between-person variation in treatment effects being only about one tenth the variance of background within-person variation.
The performance of the neural network is similar to those obtained in the previous section, as summarized in Table 1 (model 2): The variance reduction is even slightly larger (around 45%), as well as the coefficient of determination between predictions and original simulation results (0.86).
This result holds regardless of whether outlying data points are included or not (the difference in variance is significant even if the two most outlying data points with respect to the evolvability index are removed from both halves of the data set).
Accounting for variance in treatment effects is even more pertinent under higher levels of environmental uncertainty.
Since the number of lines composing the RIL generation is typically large since this determines the power of QTL mapping with RIL populations, the genetic effect variance reduction from using RIL equations is even greater than the reductions using equal variances for all generations illustrated in Table 2.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com