Question: he trucking example we discussed this week has a regression equation shown below. y^=0.1273+0.0672x1+0.6900x2 The following shows part of the regression output for the Trucking

he trucking example we discussed this week has a regression equation shown below. y^=0.1273+0.0672x1+0.6900x2

The following shows part of the regression output for the Trucking company example discussed in this week.

Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 0.1273 0.205203 0.620541 0.535378 -0.2764999 0.531174204
Miles 0.0672 0.002455 27.36551 3.54E-83 0.06235038 0.072013099
Deliveries 0.6900 0.029521 23.37309 2.85E-69 0.63190133 0.748095234

What conclusion can you reach using the p-value 3.54E-83?

Group of answer choices

there is a linear relationship between miles and total time traveled

there is not a linear relationship between miles and total time traveled

there is a linear relationship between the number of deliveries and total time traveled

there is not a linear relationship between the number of deliveries and total time traveled

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