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VoiceOfRa comments on Starting University Advice Repository - Less Wrong Discussion
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Here is how this game works. We have a bunch of observed variables X, and a smaller set of hidden variables Z.
We assume a particular model for the joint distribution p(X,Z). We then think about various facts about this distribution (for example eigenvalues of the covariance matrix). We then try to conclude a causal factor from these facts. This is where the error is. You can't conclude causality that way.
Yes, you can. You can conclude that some causal factor exists. You then define g to be that causal factor.
No you can't conclude that. I am glad we had this chat.
So you're saying that the fact that all these traits are correlated is a complete coincidence?
Look Eugene, I am not super interested in getting into an internet argument with you and your army of downvoting sockpuppets. What I am saying is you don't understand how causality is concluded from data. Maybe you should read about it sometime.
Oh, I do. How about you read up on IQ research sometime.
What if there are several such causal factors?
The correlation studies that lead to defining IQ suggested that there is a single one, or if there multiple, they themselves are strongly correlated with each other.