brandonhsi Wrote:Hello,
I want to confirm my understanding of necessary accumptions for causation. Thanks!
Conclusion:
A cause B
Necessary assumptions:
B does not cause A (that the reverse is not true).
C (third element) does not cause A and B (that some third element doesn't cause both).
A and B have some impact on one anther.
The following are NOT necessary assumptions, but can be used to weaken (not cripple, just weaken) the conclusion?
Cause happens without effect
Effect happens without cause
Finally, I shouldn't treat causation as conditional language? In other words, A causes B could be written like conditional logic A --> B?
I assume you mean all this for questions involve correlation but conclude causation.
If I read A and B happen together and that therefore A causes B, it's necessary to assume that they aren't actually both caused by a third thing. Technically, it'd be OK if A and B are both caused by a third thing, as long as A also causes B. But, if there's a third thing causing them, the argument won't make sense--the conclusion might be true, but it's not definitively proven by the premises.
Similarly, it's OK if B causes A,
as long as A also causes B, but the fact that B causes A would definitely weaken the argument. But, in order for us to conclude that A causes B just from a correlation, we have to assume that B doesn't cause A. Again, it doesn't make the conclusion impossible, it just makes the argument senseless (why conclude A-->B from A & B if B --> A?).
Yes, it's necc. to assume that they have some impact on each other (i.e. the correlation relates to SOME causation).
The two last bits you wrote are indeed ways to weaken or destroy a causal argument based on correlation. (Remember, we're weakening arguments, not conclusions.)
As for whether you should write causation as a conditional, it's fine to do so if that helps you. Can we think of A causes B as if A then B? Yes.