All of krzhang's Comments + Replies

krzhang20

I'm glad it was helpful. =)

krzhang20

Hi Vaniver! =D

On the commentary: your eyeballing seems good, but I don't think I ever said anything about relative comparisons between correlation coefficients (namely just overall correlation is positive). As you observed, I could easily make all 3 correlations (blue-only, green only, or blue+green) positive. I don't have any interesting things to say about their relative degrees.

I don't quite see the difference in interpretation from this writing. I agree with basically all the stuff you've written? The fact that the slicing "behaves as a filter&quo... (read more)

1Vaniver
The main line I'm thinking of is: I don't think this story quite captures the data, because I can construct a model where both of these are true but we don't get this effect. If you have the same link between income and education for each group conditioned on knowing group membership (and a net positive relationship without knowing group membership), but you have the blue group mean only to the right (i.e. more educated) than the green group mean, then you don't have this effect because equal education lines don't have blues earning more than greens (they earn less; this is a straightforward 'discrimination against blues' story). I would use the language of B to mean "in the three node model which has color, education, and income, the direct effect of education on income is positive," which does not appear to be true in the graphs, which look like they could be generated from a E<-C->I model. While it could also be used to mean "in the two node model which has education and income, the direct effect of education on income is positive," that seems unnatural in a case where you know that the link from E to I is spurious (that is, it flows backwards along the causal path from C to E; changing your level of education can't change your color). But this could just be me expecting an unreasonable level of precision from your wording, since the straightforward interpretation, though unnatural, does fit the data (although I think it reduces the strength of the "this doesn't show discrimination" claim, because it does show that what looked like a virtuous education-income link is now a questionable color-income link). It's very possible I've imagined the difference / misunderstood what you've written. My appreciation of the filtering effect of the slices is also very recent, and I may think it's more important as I think about it more. It seems that I'm quick to jump to a graphical model with nodes that captures the effects between these groups, and want to keep direct, i
krzhang00

Haha hey QC. Remind me sometime to learn the "get ridiculously high points in karma-based communities and learn a lot" metaskill from you... you seem to be off to a good start here too ;)

3Qiaochu_Yuan
Step 1 is to spend too much time posting comments. I'm not sure I recommend this to someone whose time is valuable. I would like to see you share your "street rationalist" skills here, though!
krzhang150

I am Yan Zhang, a mathematics grad student specializing in combinatorics at MIT (and soon to work at UC Berkeley after graduation) and co-founder of Vivana.com. I was involved with building the first year of SPARC. There, I met many cool people at CFAR, for which I'm now a curicculum consultant.

I don't know much about LW but have liked some of the things I have read here; AnnaSalamon described me as a "street rationalist" because my own rationality principles are home-grown from a mix of other communities and hobbies. In that sense, I'm happy to... (read more)

2Qiaochu_Yuan
Welcome! It's good to see you here.