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As a first step, an experimental setup was developed that isolated dataset composition as the sole factor of variance influencing VS performance.
The strongest factor of variance is represented by the horizontal axis, the second strongest factor by the vertical axis.
While the first principal component axis (PC1) accounts for the majority of variation (51%), and thus conveys a large part of the information contained in the data, the second principal component axis (PC2; Figure 3) which holds the second strongest factor of variance, only accounts for 12% of the variation.
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Cantilevers were considered as a factor in two-factor analyses of variance, the other factor (and main factor of interest) being crystal face.
Patient derived factors of variance such as fasting, exercise and particularly medication, may be expected to show a considerable influence on biomarker levels seen.
Results were analysed using two-factor analysis of variance, the factors being oestrogen-absent or present- and progesterone-absent or present.
Single factor analysis of variance (ANOVA) was used to calculate the significant difference.
Through single factor analysis of variance, Question 11, Question 15, Question 19 and Question 22 were found differ among groups.
Statistical analysis of data was accomplished by one factor analysis of variance (ANOVA).
Single factor analysis of variance (ANOVA) was used to evaluate quantitative differences of FISH detected cells between the sludges.
Data were analyzed by the ANOVA statistics program using a two factor analysis of variance of repeated measures.
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