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The qualifications of an incoming academic class depend on the relationship between qualifications and admission (decision by the school whether to admit), as well as the relationship between qualifications and matriculation (decision by an admitted student whether to attend). This Demonstration shows the effects of different admission policies and different matriculation decisions on the "class profile": the distribution of qualifications among the students that end up attending.
The grayish curve is the relationship between the criteria (like SAT score or GPA) and the probability of being offered admission. The orange curve is the relationship between the criteria and the probability that a student offered admission will accept ("matriculate"). The brown curve is thus the probability that a student with a given criteria will end up attending the school. Change the curves by dragging the locators.

DETAILS

To actually use this model, you need to convert all data to applicant percentile data, i.e. students with a score of 163 have a score that is at least as good as 81% of applicants and students with a score of 153 have a score that is at least as good as 43% of applicants. You also need to assign values for the probability of admission for applicants and the probability of matriculation for admitted students with these percentile rankings of scores. The model then determines the fraction of applicants that matriculate and the distribution of percentile scores among matriculants. This Demonstration outputs the mean, 25th percentile, 50th percentile (median) and 75th percentile scores.
Snapshot 1: a school with some problems in attracting students
Snapshot 2: a very strong school
Snapshot 3: an average school

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