Sentence examples for causation variables from inspiring English sources

In the causal directed acyclic graph (DAG) approach, an arrow connecting two variables indicates causation; variables with no direct causal association are left unconnected.

However, correlation does not necessarily indicate causation; two variables may be related to each other, but this does not confirm that one variable causes the other.

This schema represents causation between variables, with directions of influence depicted by arrows.

Finally, inferences about causation between variables cannot be raised because of the cross-sectional nature of data.

Toda Yamamoto version of Granger causality has been employed to establish the causation amongst the variables.

In addition, there is plainly some causation among social variables, notably from education both to higher income and to higher occupational status.

They are prone to extraordinary delusions and equally immense blindspots: spurious correlations, backwards causations or confounding variables cause them to see things which aren't there and to ignore things which aren't.

In the results that follow, it is important to note that the context of causation and interlinkage amongst variables is inadequately known; there may be spurious correlations or significant relationships that are influenced more by lurking variables rather than the two variables identified.

Causation requires possible lurking variables to be carefully controlled for by random selection of representative experimental subjects.

Due to the cross sectional nature of this research, it is not possible to infer causation between the measured variables and intentions to seek help.

The effect of such changes is that correlation becomes causation, i.e. variables that happen to be both active at the same time (e.g., because they are stimulated by the same external conditions) become causally related by connections internal to the system, and thus their behaviour becomes more correlated in future.