Is this calculation showing that, with a big causal graph, you’ll get lots of very weak causal relationships between distant nodes that should have tiny but nonzero correlations? And realistic sample sizes won’t be able to distinguish those relationships from zero.
Andrew Gelman often talks about how the null hypothesis (of a relationship of precisely zero) is usually false (for, e.g., most questions considered in social science research).
Is this calculation showing that, with a big causal graph, you’ll get lots of very weak causal relationships between distant nodes that should have tiny but nonzero correlations? And realistic sample sizes won’t be able to distinguish those relationships from zero.
Andrew Gelman often talks about how the null hypothesis (of a relationship of precisely zero) is usually false (for, e.g., most questions considered in social science research).
Yeah, that’s the thing I’m most worried about as well, and what the last part of the question is about. I tried to check whether more samples obviously drive the number of causal non-correlations down, but only eye-balling it doesn’t suggest this.