Response:
b. We anticipate that each additional dollar spent on tutoring will lead to an increase of 1.5 points in the exam score, assuming the weekly sleep hours and study hours are kept constant.
Detailed explanation:
Greetings!
In the context of any multiple regression analysis, the slope can be described as "the adjustment in the predicted average of Y when one of the independent variables increases by one unit, with the others held steady.
In this scenario, the dependent variable is:
Y: Exam score
While the explanatory variables are:
X₁: teacher’s salary ($).
X₂: weekly sleep hours of a student.
X₃: study hours of a student.
The resulting model can be expressed as ŷ = 65 + 1.5X₁ + 0.2X₂ + 0.5X₃
You should interpret the slope for the amount paid to the teacher b₁ = 1.5
The slope's units equate to units of Y per units of X, where Y is dimensionless, thus represented as 1/$.
Consequently, we can conclude that for every extra dollar given to the tutor, the predicted average exam score will rise by 1.5 per 1/$, as long as the hours of sleep and study are consistent.
I hope this is useful!
