Reverse Engineering GPA Distributions from Honors Data
Reverse Engineering GPA Distributions from Honors Data
Sometimes universities decline to publish the distribution of grade point averages (GPAs) of their students. Such schools often publish, however, the grade point averages attained by students at various levels of "honors". The school might say, for example, the top 30% of students had GPAs of at least 3.3 and the top 15% of students had GPAs of at least 3.5. This Demonstration shows how the overall distribution of GPAs can be reverse engineered from such honors data. You select two data points to correspond with two levels of honors. The Demonstration responds with its best estimate of the cumulative distribution function of grades.