Insight on Admissions: By the Numbers

Previous Posts in This Series:

• An Introduction
  

Let’s suppose you and 7 friends were sitting around a conference table in front of a box with roughly 150 applications in it. Each application is over 20 pages long including letters of recommendation, transcripts, personal statements, and at least 5 pages of useless information required by the graduate school. You have only 24 hours in a day and only 30 days to make your decisions. Everything else in your life continues exactly as is has previously. How would you go about deciding which 30 were your favorite?

That’s essentially how our admissions committee started things this year. The four graduate students on the committee decided to each review at least half of the applications, so every application got looked at a minimum of twice. The faculty generally started at the top of the physics GRE scores and worked their way down the list. After meticulously studying every aspect of about two dozen applications, it became very clear to me that there were some very good indicators of just how much time I really needed to spend on any given application. Here are a few ways to get to the top of the pile:

1. Physics GRE percentile over 75
2. Math and physics GPA of over 3.9
3. Significant research experience with a great letter from your research adviser

And here are a few ways to get to the bottom of the pile:

1. Physics GRE percentile under 15
2. Multiple general GRE percentiles under 50
3. GPA hovering right around 3.0

Of those six indicators, you’ll note that 5 of them are strictly quantitative (I’ll talk about letters of recommendation in a later post). So in many ways, admissions really is largely about numbers - GPA’s and GRE scores. So if you want to get into the graduate program of your dreams, work on bringing up those numbers.

After it was all said and done, we had read all the applications, crunched the numbers, pondered the wording on letters of recommendation, and made the decisions on who got it and who didn’t, we went back and crunched the actual numbers to see if we could find some statistic that could differentiate between those admitted and those not. Ideally if we plotted this magic statistic on the x axis and the probability of admission on the y axis we would get a step function - everyone below some cut-off would be out and everyone above the cut-off would be in.

It actually turned out this time that the closest thing to a magic statistic was:

If you came out above some cut-off value, you had a roughly 70% chance of being admitted. If you came out below the cut-off you had something like a 4% chance of admission. It’s not a perfect measure, but it’s pretty darn good. More technically, it is necessary but not sufficient to have these quantitative measures on your side. The numbers really do matter. GPA and GRE scores really do measure in some way the overall quality of an application.