GoBruins wrote:
I have several problem with the spread sheet actually. (don't flame me, this is just my observations to help make it more accurate)
1. You went into depth of how you derived 1940, however the top 1% is actually of the total exams taken, so it should be 1% of 220,000 exams taken, so 220,000. (there is more than 1% of the population with a 99th percentile)
2. You used the full time enrollment at each school, which is 2 classes, however you're only using 1 year of exams. So your enrollment needs to 1 year acceptances and compared with 1 year GMAT totals.
3. You're stating that 10% of kellogg has 99th percentiles based on the 80% range of 660-760, however that means that AT LEAST 10%, you're not including the portion of the students are part of the middle 80% and recieved a 760. Given Kellogg's enrollment of 22% 750+, I would even guess that 14-18% are 99th percentiles. Much higher in other school I believe, since I think kellogg's emphasis on GMAT might be less than some of it's counterparts.
4. This is now an assumption, but I feel 35%acceptance rate is too low, I've seen the MonkBent analysis where 33% sounds likely, but that is to one school, I would think no matter how great a candidate, most candidate gets rejected at a school or two. So I think 35% at kellogg + xx% at chicago + XX% columbia should be closer to 65%. If you removed indians and chinese, it should be even higher.
I agree that these are valid concerns, but in many cases, I tried to deal with them.
1. Since the schools are reporting the people at their programs, I had to get the number of discrete test takers to figure it out. Also, I assumed an even distribution of top 1% across the spectrum of retesters - since it's just as likely that someone retook to get a 99th percentile as took only once. (or at least, I don't have the skills to come up with an analysis saying that people who get 740 don't retest because their scores are high enough, but people who get 680 might retest and eventually get to 760. I agree that neither scenario is likely, so it's probably true that the number of people with high GMAT scores is greater than 1% of the population, but I can't make a strong argument for that either way.
2. I used enrollment over one year (total FT MBA Enrollment / 2) except in the cases of IMD and INSEAD - so i'm accounting for one year's worth of acceptances there.
3-4. I agree with you on both counts. I imagine that the range of scores at Kellogg is probably something like top 8% = 770+, top 9%-15% = 760, and so on. That would make the range 15% of a class at Kellogg, which would clearly make the population bigger. But I don't have any data to validate that, so I didn't build that in. I think this is definitely more of a 'worst-case' type of thing. The actual percentage of top scorers at top schools is probably much higher.
Of course, taking the next step to determine what that does for one's candidacy, we'd need to determine the degree of correlation vs. causation between high GMAT scores and achievement. Anyone have any thoughts?
Edit: I went back to the spreadsheet and added middle and high estimates. Those schools at the lower end of the spectrum didn't change much, because their percentage of top 1%ers is necessarily capped at 10. My middle and high estimates came out to 43.4% and 52.2% respectively, which seems pretty reasonable when you count in the people who take it and never go to school (GMAT tutors, for example), those that get mighty scholarships at schools like Tepper and Mendoza, those that do PhD programs, and those that drop the ball in some other way (major a-hole in the essays, for example). All-in-all, I would say that the prognosis is pretty good for those with super high scores who are willing to put in a lot of work.
Also, since I didn't mention it before, this doesn't include chances of acceptance at a school like Kellogg (I think somebody posted that on here a while ago), but rather the STUDENT BODY at any given school. Given the need to manage yield, I would say that this bodes pretty well for acceptance at top schools, since my analysis only covers those who accept offers--the percentage of 1%ers who are accepted to each school is probably comparatively higher.