A business statistics professor would like to develop a regression model to predict the exam scores for students based on their current GPAs, the number of hours they studied for the exam, and the...

A business statistics professor would like to develop a regression model to predict the exam scores for students based on their current GPAs, the number of hours they studied for the exam, and the number of times they were absent during the semester.  The data for these variables is attached.

a) Run the multiple regression in Excel.  Hint: set x₁ = GPA, x₂ = Hours, X₃
= Absences.

b) Find the R²
and explain its meaning.

c) Explain the outcome of the F test.  What does it mean?

d) Explain the outcomes of the t tests for the slope coefficients.

e) Write out the regression equation.

f)  Explain the meanings of the slope coefficients.

Extracted text: Score GPA Hours Absences 68 2.53 3.00 69 2.25 4.00 3 70 2.60 2.50 1 71 3.10 0.50 74 3.08 6.00 4 77 2.75 3.50 6 77 3.35 1.50 78 2.98 3.00 3 78 2.99 2.00 3 79 2.84 2.50 2 79 2.80 4.50 82 3.44 7.00 1 83 3.25 3.00 1 84 3.15 3.00 4 84 3.18 5.50 84 2.95 2.00 84 2.71 4.00 1 85 3.20 4.50 85 3.75 2.00 85 3.57 3.50 2 86 2.92 6.00 1 86 3.04 6.50 1 86 3.16 5.00 87 3.89 7.50 4 87 3.54 4.00 89 3.33 6.50 1 89 3.66 5.00 90 2.87 3.50 90 3.40 6.00 1 91 3.22 4.50 91 3.79 7.00 92 3.93 6.00 2 92 4.00 5.00 92 3.60 6.50 1 93 2.98 4.00 2 94 3.26 6.50 98 2.88 3.50 99 3.73 5.00 1 100 3.48 6.50 1 100 3.00 7.00