Score GPA Hours Absences Gender78 3.15 3.0 4 Female75 2.71 4.0 1 Female79 3.57 3.5 2 Male85 3.26 6.5 0 Female85 3.75 2.0 0 Female84 3.20 4.5 3 Female85 3.16 5.0 3 Male80 3.35 1.5 0 Female74 2.75 3.5 6 Male81 3.04 6.5 1 Male76 2.53 3.0 0 Female85 2.92 6.0 1 Male A business statistics professor would like to develop a regression model to predict the final exam scores for studentsbased on their current GPAS, the number of hours they studied for the exam, the number of times they were absentduring the semester, and their genders. The data for these variables are given in the accompanying table. Completeparts a through e below.Click the icon to view the data table.a. Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen,which equals 1 for a male and 0 for a female student (this assignment is arbitrary).Complete the regression equation for the model below, where y = Score, x₁ = GPA, x₂ = Hours, x3 = Absences, andX4 = Gen.ŷ=+(x₁+x₂ + (x3 +×4(Round to two decimal places as needed.)

Here the dependent variable (y) is the Score for students.There are four independent variables:x1 =…

a. Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student (this assignment is arbitrary). Complete the regression equation for the model below, where y=Score, x₁ =GPA, X₂ = Hours, x3 = Absences, and X4 = Gen.

a. Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student (this assignment is arbitrary). Complete the regression equation for the model below, where y=Score, x₁ =GPA, X₂ = Hours, x3 = Absences, and X4 = Gen.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

Score GPA Hours Absences Gender
78 3.15 3.0 4 Female
75 2.71 4.0 1 Female
79 3.57 3.5 2 Male
85 3.26 6.5 0 Female
85 3.75 2.0 0 Female
84 3.20 4.5 3 Female
85 3.16 5.0 3 Male
80 3.35 1.5 0 Female
74 2.75 3.5 6 Male
81 3.04 6.5 1 Male
76 2.53 3.0 0 Female
85 2.92 6.0 1 Male

A business statistics professor would like to develop a regression model to predict the final exam scores for students
based on their current GPAS, the number of hours they studied for the exam, the number of times they were absent
during the semester, and their genders. The data for these variables are given in the accompanying table. Complete
parts a through e below.
Click the icon to view the data table.
a. Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen,
which equals 1 for a male and 0 for a female student (this assignment is arbitrary).
Complete the regression equation for the model below, where y = Score, x₁ = GPA, x₂ = Hours, x3 = Absences, and
X4 = Gen.
ŷ=+(x₁+x₂ + (x3 +×4
(Round to two decimal places as needed.)

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