Consider the linear regression models. The p-values are shown in parenthesis.Model 1 Y = 123.2 + 0.89X1(0.0005) (0.00001)R2 = 0.600Model 2 Y = 40.1 + 0.14X2 + 0.61X3(0.003) (0.008) (0.0004)R2 = 0.825Model 3 Y = -1.7 + 2.57X1 - 1.78X2(0.006) (0.1) (0.2)R2 = 0.876Where Y are the number of trips, X1 is the total employment, X2 is the industrial employment, X3 is the commercialemployment. Choose the most appropriate model and explain in writing why this model is selected as the most appropriatemodel. Consider both goodness-of-fit and coefficient significance

Engineering Fundamentals: An Introduction to Engineering (MindTap Course List)
5th Edition
ISBN:9781305084766
Author:Saeed Moaveni
Publisher:Saeed Moaveni
Chapter15: Computational Engineering Tools Matlab
Section: Chapter Questions
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Consider the linear regression models. The p-values are shown in parenthesis.
Model 1 Y = 123.2 + 0.89X1
(0.0005) (0.00001)
R2 = 0.600
Model 2 Y = 40.1 + 0.14X2 + 0.61X3
(0.003) (0.008) (0.0004)
R2 = 0.825
Model 3 Y = -1.7 + 2.57X1 - 1.78X2
(0.006) (0.1) (0.2)
R2 = 0.876
Where Y are the number of trips, X1 is the total employment, X2 is the industrial employment, X3 is the commercial
employment. Choose the most appropriate model and explain in writing why this model is selected as the most appropriate
model. Consider both goodness-of-fit and coefficient significance 

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