Sentence examples for between the variable sets from inspiring English sources

Accordingly, we can reject the null hypothesis that there was no relationship between the variable sets and conclude that there probably was a relationship.

The effect size was 0.936, which indicates that the full model explained a substantial portion of 93.6 %, of the variance shared between the variable sets.

Function 3 to 3 (which is the only function that was tested in isolation) did not explain a statistically significant amount of shared variance between the variable sets, F (2174) = 1.885, p = 0.155.

Thus, for the set of three canonical functions, the r 2 type effect size was 0.936, which indicates that the full model explained a substantial portion of 93.6 %, of the variance shared between the variable sets.

Thus, for the set of 10 canonical functions, the r2 type effect size was.79, which indicates that the full model explained nearly all, about 79%, of the variance shared between the variable sets.

All of these differences were associated with Rotation Design 2, which means that the correlations between the variable set and performance in one of the rotated forms were consistently higher than the correlations in the other rotated form.

In contrast, this qualitative assessment means the starting point for the current proposed quantitative methodology, because it allows us to move progressively towards obtaining a pure quantitative model, based on the relationships between the variables set by the Bayesian network model and the gradual incorporation of new quantitative data.

Both CT-SVM and SMVCCAE/SSMVCCAE utilize the ρ correlation coefficient calculated in CCA which measures the correlation/similarity between the two variable sets in each dimension.

CCA was conducted using the three input variables (R&D expenses in absolute dollars ; R&D expenses as percent of revenues; pipelines valuation as percent of total valuation) as predictors of the four performance variables (i.e., revenues, market valuation, net income, price-earning ratio) to evaluate the multivariate-shared relationship between the two variable sets.

Three factors that correlated highly between the two variable sets were found.

CCA aims to maximize the similarity between two variable sets by projecting them onto a correlation subspace.