A statistics student wants to determine if there is a relationship between a student's number of absences, x, and their grade point average (GPA), y. The given data lists the number of absences and GPAs for 15 randomly selected
students.
15
1
0
6
9
12
3
3
1
2
7
0
4
9
10
Number of
Absences
GPA
2.14.3 4.5
3.2
4.0
1.7
3.8
2.9
3.6
3.4
2.6 3.1
2.8
2.8 4.1
Using technology, the y-intercept is
4.5, which means a student with no absences has a GPA of 4.5.
4.5, which means a student with no absences is predicted to have a GPA Ôt 4.5.
3.79, which means a student with no absences is predicted to have a GPA of 3.79.
3.79, but it does not make sense to interpret the y-intercept in this context.