Read the following description of a data set.

Question

Hanson manages the student health services department at Fairfax University. He suspects that the students' poor breakfast habits are contributing to the school's academic decline. Hanson surveyed several students asking how many times they ate breakfast in the past month. He also checked each student's GPA.
The data shows the number of times each student ate breakfast in the past month, x, and his or her GPA, y.
The least squares regression line of this data set is:
y=0.047x+2.719
What GPA does this line predict for a student who ate breakfast 17 times this past month?
Round your answer to the nearest thousandth.

Answer 1

Using the equation of the least squares regression line, we can plug in x=17 to find the predicted GPA:

y = 0.047(17) + 2.719
y = 0.799 + 2.719
y = 3.518

Therefore, the least squares regression line predicts a GPA of 3.518 for a student who ate breakfast 17 times in the past month.