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By reducing data, this technique is used to explain the variability among observed variables in terms of a smaller number of non-observed variables called factors.
However, the calculation of the heterogeneity of variables highlights the variability among the studies.
Factor analysis was used as it takes into consideration the variability among observed variables.
Target levels for acute treatment were more variable, which is in accordance with the variability among guidelines (Malhi et al. 2017).
Overall, the variability among eco-regions was higher than the variability among fire weather scenarios, and among replicates.
There are several possibilities to explain the variability among the isolates.
This data collection process was also intended to capture the variability among readers.
Results showed that student discipline and treatment length explained part of the variability among treatment effects.
If the rankings are in perfect agreement, the variability among sums will be a maximum (Mattson [1986]).
The variability among treatments (1.27‰) was smaller than the variation within the early-season drought treatment (3.06‰).
Moreover, Q-mode factor analysis after Varimax rotation was performed to check the variability among the tobacco products.
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