Conditional statements don't really work because "if A, then B" means that A is sufficient for B, but "A causes B" doesn't imply that A is sufficient for B. E.g. in "Smoking causes cancer", where smoking is a partial cause for cancer, or cancer partially an effect of smoking.
"A causes B" usually implies that A and B are positively correlated, i.e. P(A and B) > P(A)×P(B), but even that isn't always the case, namely when there is some common cause which counteracts this correlation.
Thinking about this, it seems that if A causes B, the correlation between A and B is at least stronger than it would have been otherwise.
This counterfactual difference in correlation strength is plausibly the "causal strength" between A and B. Though it doesn't indicate the causal direction, as correlation is symmetric.
Comments
Conditional statements don't really work because "if A, then B" means that A is sufficient for B, but "A causes B" doesn't imply that A is sufficient for B. E.g. in "Smoking causes cancer", where smoking is a partial cause for cancer, or cancer partially an effect of smoking.
"A causes B" usually implies that A and B are positively correlated, i.e. P(A and B) > P(A)×P(B), but even that isn't always the case, namely when there is some common cause which counteracts this correlation.
Thinking about this, it seems that if A causes B, the correlation between A and B is at least stronger than it would have been otherwise.
This counterfactual difference in correlation strength is plausibly the "causal strength" between A and B. Though it doesn't indicate the causal direction, as correlation is symmetric.