If you were among the 950 or so lucky round one MBA applicants who received an invitation earlier this month to interview with Harvard Business School, what are your chances of getting an actual acceptance from the school?
That depends, of course, on how well you do in the face-to-face interview with HBS admissions officials. But Wayne Atwell believes your odds of getting an admit letter are roughly 50-50. Atwell, a self-styled data geek, is a second-year MBA student at New York University’s Stern School of Business. Attwell did his undergraduate degree in engineering and worked in strategy and marketing analysis for more than six years in financial services. His post-MBA goal is to land a job at a top consulting firm. One thing is certain: He loves swimming in data.
Passionate about numbers and analysis, he put up a blog called MBADataGuru.com where he grabs info off of GMAT Club forums, plugs them into Excel spreadsheets and comes up with all kinds of odds and stats. Attwell readily admits that his observations are based on roughly 10% of the applicants who share their input on the Internet forums. And he puts a disclaimer on his analysis: “Results may not be 100% accurate,” concedes Atwell, “and are meant to give you a rough idea of your chance of admission.” Yet, Atwell’s observations, if not entirely authoritative, at least have amusing entertainment value, particularly to stressed out and anxious applicants who obsess over getting accepted into a top business school.
HIGHEST INTERVIEW ACCEPTANCE RATE: ATWELL SAYS STERN ACCEPTS 75% OF INTERVIEWEES
He says, for example, that his own school has the highest acceptance rate for applicants who are granted an admissions interview: 75%. In fact, among the top-tier schools, the most likely to send an admit letter to an interviewee besides Stern are UCLA’s Anderson School of Management (68%), Cornell University’s Johnson School of Business (67%), UNC’s Kenan-Flagler Business School (67%), and the University of Virginia’s Darden School of Business (65%), according to Atwell.
The schools with the lowest interview acceptance rates? Obviously, Northwestern University’s Kellogg School of Management, largely because it is the only top-rated school that seeks to interview every candidate, and Dartmouth College’s Tuck School of Business, mostly because it invites anyone who wants an interview to have one. At Kellogg, Atwell pegs the rate of admission for interviewees at 34%. At Tuck, he thinks it is 36%.
Besides Kellogg and Tuck, applicants who get interviews at Stanford University’s Graduate School of Business face the toughest odds of admission. Atwell estimates a candidate’s Stanford chances at 46%, just a sliver below Wharton’s 47%. Of course, Stanford is the most highly selective MBA program in the U.S., with an actual acceptance rate of just under 7% for the 7,899 applicants to the school for the Class of 2017.
ATWELL SAYS A 800 GMAT INCREASES YOUR CHANCES OF ADMISSION TO STANFORD GSB TO 20%
More compelling are the data gymnastics Atwell performs on correlations between GMAT and GPA scores and acceptances. In a recent post, for instance, he calculated that an applicant to Stanford who increases his or her GMAT by 100 points, from 650 to 750, hikes their chance of admission by eight-fold. Candidates to Stanford with a perfect GMAT score of 800, estimates Atwell, have a 20% chance of being admitted to the school’s MBA program, nearly three times the actual acceptance rate. At Yale’s School of Management, he calculates, an 800 will get a candidate a whopping acceptance rate of 59%.
If your GMAT is 790, your chances of a Stanford admission fall to 17%. At 780, it’s 14%; and at 770, it’s 12%. A 4.0 GPA would boost an applicant’s acceptance rate to 10%, thinks Atwell. Derrick Bolton, Stanford’s director of MBA admissions, would surely contest those numbers. But that doesn’t make them less compelling. Interestingly enough, these latest projections by Atwell on how GMATs and GPAs impact admission decisions at Stanford are not his first. Atwell says he was less than happy with an original predictive model he built for Stanford, and he explains his rationale in terms that would make any stats professor keen to give him an A in the class.
“I updated my methodology for building the model, mainly in the way I cleaned the data,” he explains on his blog. “In order to evaluate performance, I grouped applicants into buckets based on their predicted acceptance rate, then looked at the actual acceptance rate was for that group. The X-axis is the predicted acceptance grouping and the Y-axis is the actual acceptance rate.”