Summer Stat 113 Part D-Olivia Lam

Summer Stat 113 Part D-Olivia Lam - Project Part D Olivia...

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Project Part D Olivia Lam Professor Liang In Part D of this project I will be discussing six important pairs of variables that will be useful for the University of West Erlham County. The six important pairs that I will be using to compare to each other in order to help admissions to figure out which students best fits the role of being successful in our school are HSP & GPA; GPA & Residency; Credits & Class; HSP & English ACT Scores; Math & English ACT Scores, and Age & GPA. Therefore, by comparing these variables together this will give us a clear result on which students we should determine that best fits the requirements of being able to perform well within our university. HSP and GPA As you can see there is a positive correlation between the variables of GPA and HSP in the regression graph above. Although the correlation is strong between HSP and GPA, there are also many students who did excellent during their high school but did not do so well in college or vice versa. 11
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For an example, you can see that there is one student who got an 80 in their High School Percentile but then got a GPA of a 2.0, with this we can be certain that it is unlikely we will choose this student due to their GPA being low. Another example shows a student with a low high school percentile of 30 while earning a high GPA above a 3.5. Eventually, this student is bound to be one of the students we are likely to look for in determining who will be able to perform well at our school. Therefore, this information can help admissions in selecting student's success by looking at students HSP and GPA and predicting if the outcome of them being successful is high while having them maintaining a decent grade point average. In relation to my findings I suggest that the admissions should determine which students they should select by looking over student’s GPA than students HSP in predicting student’s outcome of success. Students who has decent GPA should be resulting in having higher percentile than students who have GPA that are lower. Even though there are some outliers in this graph, it is certain that there is a linear relationship between these two variables.
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