For GSB, odds of an interview. From 2009 data, source admissions411
Coefficients in question, 1 equating to interview, 0 equating to not.
Intercept -0.460851231
GMAT 0.003873504
VERB 0.0023856
QUANT -0.029936274
TIMES TAKEN 0.066353128
AGE -0.001569024
GPA 0.215000635
Where's nationality and job function you ask? I'm too lazy to map them to values and use them as dummys. Maybe if i get unlazy I'll do it.
From 2008 data, odds of acceptance, assuming unknown = ding. Again 1 equating to accept, 0 to not.
Coefficients
Intercept -0.501643016
GMAT 0.000804336
VERB 0.008032123
QUANT -0.005540867
TIMES TAKEN -0.023042997
AGE -0.026421802
GPA 0.260872977
ALUMNI RECS 0.015136345
This is decidely disconcerting if there's any truth to it. It places my odds at
pretty crappy right now.
On the other hand, Adjusted R Square 0.08175456
The whole thing means nothing, cause I did a sloppy job.
Some other tidbits I need to do to add some value:
Set up an over 21 proxy for the age or change it to years of exp assuming a 21 year old grad date. (Right now the implication is being 10 years old increases my odds)
Setup proxy for industry and country.
Pull in a much larger data set across the top 20 schools and see what happens with a data set on the order of 2000+
Maybe if I have some time tomorrow I'll do it.
Ok i did the work exp thing. No real change here -
Coefficients
Intercept -1.056500848
SCORE 0.000804336
VERB 0.008032123
QUANT -0.005540867
TIMES TAKEN -0.023042997
WORK EXP -0.026421802
GPA 0.260872977
RECS 0.015136345
Implication is that there is some bias against age. The whole data blows because all I have is 700+ to begin with, so its crap. Someone find me data sets in the 600 range.