[fats_tromino]

Just as two quick comments, confidence intervals != prediction intervals. One gives a range around a true mean value, the other gives a range around where the variable may actually fall (prediction intervals are bigger).

You may also want to mention adjusted R^2 as a measure of quality of the model. I've never heard of AICR before, the standard metrics for quality of the model are AIC/BIC (and sometimes Mallus Cp).

Edit: fixed sloppy wording about confidence interval.

[glaugh]

The prediction interval thing was sloppy, good catch.

The r^2 and AICR comments reflect the fact that these docs were built around Statwing's regression capabilities, which default to m-estimation instead of OLS. There's no adjusted r^2 for that, which I agree is a better measure when available, and it uses AICR, where the R stands for "robust". But still a good catch, since I didn't caveat ahead of time that we were only talking about robust methods (and we don't note it in the docs).

Much appreciated.

[hooloovoo_zoo]

OLS is an M-estimator.

[stdbrouw]

AIC depends on residual variation just like R^2, so I guess some people might be inclined to call it AIC_R to make that clear. Also, it's Mallows' C_p :-)

[fats_tromino]

Thanks for the clarification about Mallow's C_p, I always get the name messed up for some reason.

[fnbr]

Hey, just FYI, your posts are getting killed for some weird reason. See:

http://imgur.com/FmBkqgo

[fats_tromino]

Thank you, I'm confused as to why this is happening.