"direction of the correlation" is a grammatically correct and commonly used phrase in written English.
It refers to the overall trend or relationship between two variables in a data set. One example of using this phrase in a sentence would be: "The study analyzed the direction of the correlation between sleep duration and cognitive function in adults over the age of 50." This sentence suggests that the study looked at whether there was a positive or negative correlation between the two variables.
It was found that the magnitude and direction of the correlation for most of the soil properties noticeably differed between the river and the land sides.
Ellipses designate the magnitude and the direction of the correlation.
The gradient of the regression lines shows the respective direction of the correlation over all counties.
The direction of the correlation is not a consensus in the literature.
The strongest polarisation between countries can be seen when we consider the strength and direction of the correlation between parents' and older siblings' involvement in Austria, where the results are the diametric opposite.
Using linear regression calculate the magnitude and direction of the correlation between variables (such as between knowledge and acceptance of biological evolution for those reporting a high amount of science education), we found that knowledge and acceptance were significantly positively correlated for all groups except those that reported no science education (Additional file 1: Table S6).
Although evolutionary rates do not significantly correlate with H, the direction of the correlations is positive and comparable in strength to that observed in the overall dataset (ρ = 0.052, P = 0.113 for ω; ρ = 0.053, P = 0.102 for dN).
The range and direction of the correlations amongst the motivational constructs were within the expected ranges and directions seen in previous studies (e.g. Marsh et al. 2013).
Based on the direction of the correlations as well as Baur and Lucey (2009)'s analysis, there are four types of interdependence, as follows (Table 1).
The correlations between PM10 and HFRS were significant in univariate analyses, although the direction of the correlations changed according to the time lags.
In the univariate analyses, the associations between HFRS and PM10 were significant, although the direction of the correlations changed according to the different time lags (Table 1).
