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
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
Chapter2: Loads On Structures
Section: Chapter Questions
Problem 1P
Related questions
Question
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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