Predicting Graduate School Admission

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Predicting Graduate School Admission NICHOLAS GRABON ECE 539 12/13/13

description

Predicting Graduate School Admission. Nicholas Grabon ECE 539 12/13/13. DATA SOURCE. Self Submitted Physics only Often incomplete ~500 total data points http:// www.physicsgre.com/results.php?school=berkeley. DATA PREPARATION AND METHODS. Converted binaries to -1 or 1 - PowerPoint PPT Presentation

Transcript of Predicting Graduate School Admission

Page 1: Predicting Graduate School Admission

Predicting Graduate School AdmissionNICHOLAS GRABON ECE 539 12/13/13

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DATA SOURCE Self Submitted Physics only Often incomplete ~500 total data points http://www.physicsgre.com/results.php?school=berkeley

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DATA PREPARATION AND METHODS

Converted binaries to -1 or 1 Eliminated Data with no acceptance information Formatted GRE and grades Used svmtrain and svmclassify from class Radial basis function worked best Chose best rate out of 1000 trials Held out 100 points per trial

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DATA ANALYSIS

Chose an average resume to investigate (my own) Varied this with respect to Physics GRE score Gender Year of Application School Applied to Residency GPA And Combinations of these

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PGRE SCORE and SCHOOLClassifier Error=16%Green is accepted, blue is denied

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YEAR and PGRE SCORE

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PGRE and Gender1 corresponds to female; -1 to male

2009 2011 2013

2008

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PGRE and Race2008

2009

1 denotes ethnic minority, -1 denotes ethnic majority

2011 2013

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PGRE and Residence 0 indicates domestic; -1 is international

201320112009

2008

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PGRE and GPA

2011 Total GPA 2011 Major GPA

Here I used Princeton to emphasize the difference

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PGRE score and Verbal GRE Score

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Conclusions

The PGRE seems to be the most important factor There is a small amount of randomness but essentially

predictable Gender, ethnicity, and residence matter General GPA matters more than the subject GPA but not as much

as PGRE The top block of schools have roughly the same criteria