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Predicting Graduate School Admission

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

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Predicting Graduate School Admission

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  1. Predicting Graduate School Admission Nicholas Grabon ECE 539 12/13/13

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

  3. 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

  4. 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

  5. PGRE SCORE and SCHOOL Classifier Error=16% Green is accepted, blue is denied

  6. YEAR and PGRE SCORE

  7. PGRE and Gender 1 corresponds to female; -1 to male 2008 2009 2011 2013

  8. PGRE and Race 1 denotes ethnic minority, -1 denotes ethnic majority 2008 2009 2011 2013

  9. PGRE and Residence 2008 • 0 indicates domestic; -1 is international 2009 2011 2013

  10. PGRE and GPA Here I used Princeton to emphasize the difference 2011 Total GPA 2011 Major GPA

  11. PGRE score and Verbal GRE Score

  12. 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

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