This research examines demographic, academic, attitudinal, andexperiential data from the Cooperative Institutional Research Program (CIRP) for over 12,000 students at two universities to test a methodology for identifying variables showing significant differences between students intending to major in science, technology, engineering, or mathematics (STEM) versus non-STEM subjects. Identifying potential candidates for STEM enrollment necessi-tates a methodology for analyzing databases containing demo-graphic, academic performance, and attitudinal information acrossa wide array of students. Finding variables that are consistently significant predictors of STEM interest and capability across a range of population subgroups requires the ability to examine a large set of variables since some variables may be significant only for specific subgroups.
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nonparametric Kolgomorov-Smirnov test