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Again, aiming duration accounted for the variance in the data.
The model explained 69%% of the variance in the data.
Process indicators explained 22.5% to 30.6% of the variance in the data.
The models explain 41 65% (adj. D2) of the variance in the data.
In total, these factors accounted for 68.5%% of the variance in the data.
The results show that six factors account for 84%% of the variance in the data.
This relationship accounted for 85% of the variance in the data (Table 4).
Overall, 59.24% of the total variance in the data is explained.
All items loaded > 0.4 and explained 29.25% of the variance in the data.
Likewise, PCA computes weighted linear combinations by preserving the variance in the data.
The extents of the vertical axes show equal variance in the data across the three panels.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com