Most commonly use is Cohen's R, or even kappa.
Yule's coefficient of association measures the strength and direction of association between two binary variables. It ranges from -1 to +1, with higher values indicating a stronger association. A coefficient of 0 suggests no association between the variables.
-a to +a
Positive correlation = positive association Negative correlation = negative association
no
Correlation Coefficient.
Coefficient of multiple determination
The correlation coefficient is a measure of linear association between two (or more) variables. It does not measure non-linear relationships nor does it say anything about causality.
Although Spearman's rank correlation coefficient puts a numerical value between the linear association between two variables, it can only be used for data that has not been grouped.
A measure of association. You might be thinking of the correlation coefficient in particular.
There is no such term. The regression (or correlation) coefficient changes as the sample size increases - towards its "true" value. There is no measure of association that is independent of sample size.
A coefficient, possibly.A coefficient, possibly.A coefficient, possibly.A coefficient, possibly.
The coefficient is in front of a variable.