Research Publication Title

Modeling Grade Distribution

Major

Mathematics

Faculty Mentor(s)

Jebessa Mijena

Keywords

grade, distribution, math, statistics

Abstract

The purpose of this project is to see how various variables is associated to a student’s overall performance in mathematics courses. We look at the length of a class, level of the course and the semester the class is taken to see how these are correlated to the distribution of grades. In the beginning phase, we started out collecting data from the Georgia College grade distribution for all math classes, general math and math education for the past three semesters. We did not use online classes for the fact that they had no set length to the class which would make one of our variables nonexistent in that instance. We used a regression model to analyze the association between our variables. With this information, we used the statistical software R and a variety of its functions to evaluate the data we collected. Our goal is to show how these three variables can affect a student’s performance in the math classroom. From a few analysis, we can see that Summer of 2016 had a higher percentage of A’s, B’s, and D’s. For the spring and fall 2016 C’s had a very high percentage. Fall of 2016 F’s had the highest percentage but Spring 2016 we had a very high percentage of W’s.

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Modeling Grade Distribution

The purpose of this project is to see how various variables is associated to a student’s overall performance in mathematics courses. We look at the length of a class, level of the course and the semester the class is taken to see how these are correlated to the distribution of grades. In the beginning phase, we started out collecting data from the Georgia College grade distribution for all math classes, general math and math education for the past three semesters. We did not use online classes for the fact that they had no set length to the class which would make one of our variables nonexistent in that instance. We used a regression model to analyze the association between our variables. With this information, we used the statistical software R and a variety of its functions to evaluate the data we collected. Our goal is to show how these three variables can affect a student’s performance in the math classroom. From a few analysis, we can see that Summer of 2016 had a higher percentage of A’s, B’s, and D’s. For the spring and fall 2016 C’s had a very high percentage. Fall of 2016 F’s had the highest percentage but Spring 2016 we had a very high percentage of W’s.