If correlation doesn't equal causation, what does? And why can't you trust it even when variables are isolated? Why statistics?
>what are p-values
>what are confidence intervals
>what are double blind experiments
>if correlation doesn't equal causation, what does?
There's a correlation between women's hemline lengths and economic performance (read about hemline theory, it's actually kind of neat) but it would be foolish to say that the length of women's hemlines causes economic booms and busts (although the converse could possibly hold true).
Since everyone went for the low hanging fruit, let me ask more directly.
Where do causal links come from? When does someone get to say "yep, that's it"?
You all just say causality as if every truth was always understood and we can't find more of them.
Or are you all just saying this shit because no one knows?
Experimental designs where independent variables are manipulated and dependent ones are observed can often times be internally valid (which allows us to infer causation), rather than correlation studies where coinciding variables are studied.
There are many degrees of experimental designs which further ensure causal relationships. The best I can think of at the top of my head are double blind drug studies. Even if we weren't sure at which step the affect is produced, you be a special kind of retarded if you claimed the results are just correlation.
I know I can't thread my own comment, and I'm by no means claiming to be definitely right (look into it on your own), but given the IQ of pretty much all the other responses I'd just hedge your bets on this one.
You can reliably isolate factors with chemometrical/multivariate statistic methods.
PCA, dendrites, clusters etc. can reliably pinpoint which factors are important.