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Getting Into College the Old Fashioned Way: With Money
Businessweek (in a story spotted via Tyler Cowen's Marginal Revolution) profiles ThinkTank Learning, a college-admission consultancy founded by Steven Ma, and largely catering to ambitious Asian immigrants like Ma, and their offspring — kids who'd like to go to elite schools, and can afford to have Ma's firm help them navigate the path to getting in. It's a statistics driven system, and backed by a money-back guarantee, so long as the applicant meets certain requirements: ThinkTank will refund their tens of thousands of dollars in fees if they don't make it into the sort of school that the ThinkTank algorithms say they will. Basically, they've reverse engineered the admissions policies at schools, particularly elite schools like MIT, Stanford, and the Ivies, and done so well enough to know which factors in a student's portfolio can be tweaked to increase their odds of getting into the big-name schools. A slice: [Ma's] proprietary algorithm assigns varying weights to different parameters, derived from his analysis of the successes and failures of thousands of students he's coached over the years. Ma's algorithm, for example, predicts that a U.S.-born high school senior with a 3.8 GPA, an SAT score of 2,000 (out of 2,400), moderate leadership credentials, and 800 hours of extracurricular activities, has a 20.4 percent chance of admission to New York University and a 28.1 percent shot at the University of Southern California. Those odds determine the fee ThinkTank charges that student for its guaranteed consulting package: $25,931 to apply to NYU and $18,826 for USC.
"than", you ignorant buffoon.
Oh come on. You can do better than that. The quality of ACs has really dropped these days.
putting the 'B' in LGBTQ+
Well, I've actually written articles in peer-reviewed professional publications and essays on the topic of the use of statistics.
[citation needed]
Well, sure, if you insist. I actually participated in the founding of the discipline of combinatorics, partly to discuss issues of probability and statistics of distributions. See my treatise Ars Magna Sciendi sive Combinatoria (1669), for example.
If you dig into my earlier treatises, you'll find I actually considered a number of issues in this sort of mathematics even before Leibniz's De Arte Combinatoria (1666) (he was actually a bit of a fan of my work, I exchanged some great letters with him about it back in the day), and well before all those young Bernoulli whippersnappers got involved.
(What's that -- you wanted a serious answer? You want me to give real-world information about myself to a guy who hides as an AC?)