Or maybe a better way to phrase it: There are pairs of business schools that are clearly correlated, in terms of their attractiveness to the Brave Supplicants of the world.
Continuing our recent data derby, let’s isolate a few of the obvious with a series of charts today. We’ll start with the basics:
Then we look at this, and WOW.
Now we go to the maybe-not-so-obvious one:
That seems pretty parallel. We’re rather certain that a chunk of the Haas volume is due to the Stanford draw. People know that Stanford is awesome and they decide to apply there, and they do a modicum of research and they realize that Berkeley is in the same general geography of the beautiful Bay Area (it really is beautiful), and so they decide to try their chances at Haas, too. Not everyone who tries for Stanford goes for Berkeley – obviously there’s only half as many applying to Haas. But we’re guessing that almost everyone who applies to Haas also applies to Stanford. (The especially foolish ones consider Berkeley a “safety school”; anyone who’s got half a clue recognizes that Berkeley is almost as selective as Stanford is. Hopefully you’ve diversified beyond just these two if you have your heart set on going to bschool anytime soon.)
These geographic pairings happen elsewhere, of course. In New York City, for example:
You coulda guessed that though, right? Most people who try for Columbia also throw their hat in the NYU ring while they’re at it.
In case you’re now assuming that any two pairs we put together will show a similar pattern, let’s go the opposite direction — yet with a set of schools you may expect to see something different from:
Maybe you’d assume a loosely coupled relationship here too, but they seem much more divorced than the others. After all, they’re both in New York. They’re both Ivy League. Why wouldn’t there be the same pattern there as with Columbia-NYU?
There’s the obvious answer of rankings. Is that the extent of it or do you think there are other factors at play? We’d be interested in your thoughts on that or any of these other relationships. Feel free to post in the comments.
* EssaySnark is no statistician. We’ve don’t know that much about correlation; we’ve done no regression analysis on this data. (We’ve heard of “regression analyses” and we know they exist, but we’ve certainly never seen one in real life.) We’re just trying to make conversation about stuff that seems interesting. If you can add something to the conversation please do! Just cut us some slack that we’re not doing this analysis thing full-bore and complete-like.