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And now I've added a line, which is a least-square fit, which minimizes the sum of squared deviations from the line.
Sum of squared deviations about the grand mean across all N observations.
The sum of squared deviations for each level mean about the grand mean.
The sum of squared deviations for all observations within each level from that level mean.
A linear transformation of the X variables is made so that minimum value of the sum of squared deviations of the observed and predicted Y is obtained.
The sum of squared deviations about the grand mean across all Nobservations is given by SST T = ∑ i = 1 4 ∑ j = 1 32 x ij − μ 2 Open image in new window (6).
The sum of squared deviations of annual runoff versus time is shown in Fig. 5. Figure 5 shows that the local minima occurred in 1980, indicating that 1980 is detected as abrupt change point of runoff series.
Similar(4)
Mismatch distributions were calculated and the sum of squared deviations (SSD) and raggedness indices (r) between observed and expected mismatch distributions were used as a test statistic; their P values represented the probability of obtaining a simulated sum of squared deviation greater than or equal to the one observed.
'*', P values, 0.05; '**', P values, 0.01; SSD, sum-of-squared deviations; Rag, Raggedness index.
The sum-of-squared deviations (SSD) between the observed and expected mismatch distributions were computed, and P-values were calculated as the proportion of simulations producing a larger SSD than the observed SSD.
Wing specimens were translated to the origin, scaled to a unit centroid size and rotated around their shared centroid to minimize the sum-of-squared deviations of the coordinates from all specimens to achieve an optimal fit to the consensus (average) configuration.
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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