sorority comments

just same old bashing from all the houses

some all 5's though

since clearly to the left things are just getting out of hand.

DG/Kappa
Theta/Pi Phi
---------
Alpha Phi/TriDelt
ADPi/GPhiB
AXO

Please, thank you, goodbye.

Outside, impartial evaluation in order by popularity on campus:
Theta, Kappa, DG, Alpha Phi, PiPhi, ADPi, TriDelt, GPhi, AXO, SDT. The End

most accurate ranking so far

Theta, DG,
Kappa, PiPhi
TriDelt, GPhiB
ADPi, AXO
SDT

Here's the ultimate unbiased ranking after last fall's recruitment (ignore the prior ones clearly posted by someone trying to self-promote her house):
1. DG
2. Kappa
3. Theta
4. Pi Phi
5. APhi
6. Tridelt
7. ADPi
8. Gamma Phi
9. AChio
10.Sig Delt

In some cases, there's more of a tie between 2 houses and one of these will be above/below the other so don't feel too bad if that's your case.

Agree w GDI except seriously???? DG and Kappa are equally good after last fall's recruitment, and many would argue that Kappa did better.

No one cares about rankings except for rude elitists. The greek system should exemplify brother and sisterhood, not "we're better than you" attitudes.

Descriptive statistical tools are really just algorithms for summarizing characteristics of the distributions of scores. That is, they are mathematical operations. Where statistics really become "statistical" is on the inferential side. That is, when our attention turns to assessing the reproducibility or likelihood of the pattern that we have described. Inferential statistics can be, and are, applied to the analysis of network data. But, there are some quite important differences between the flavors of inferential statistics used with network data, and those that are most commonly taught in basic courses in statistical analysis in sociology. Suppose, for example, that I was interested in the proportion of the actors in a network who were members of cliques (or any other network statistic or parameter). The notion of a clique implies structure -- non-random connections among actors. I have data on a network of ten nodes, in which there are 20 symmetric ties among actors, and I observe