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Significance was calculated on the average signed error over the whole volume across subjects using a one-sided paired Wilcoxon signed rank test.
In both conditions, average signed error scores were low (Mean across the two path lengths were: SW = 11.7 cm and BW = 17.0 cm) and did not differ significantly from each other (t(11) = −0.54, p = 0.60; paired samples t-test).
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Mean signed error.
We carried out the analysis on the absolute errors, signed estimation errors and standard deviation of absolute estimation errors.
We first related signed TD errors, unsigned TD errors, and fictive errors over gains to task behavior.
Furthermore, we introduce a low-overhead module to reduce the relative error and a sign correction module to fix the sign error.
Results revealed an average transformation error of 3mm.
Excluding outliers, average percent error for males was 9.2%.
From these distributions, we obtain an average bit error rate (BER) of 1 error per 86.9 bits.
RealClearPolitics' simple average, which included Wednesday polls, had greater difficulty, with an average absolute error of 3.3 percentage points.
Using a machine-learning algorithm on a data set of 10 proteins and 179 mutations, we predict both the magnitude and the sign of the allosteric conformational equilibrium shift by the mutation; the impact of a large identifiable fraction of the mutations can be predicted with an average unsigned error of 1 kBT.
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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