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The Following MINITAB Output Presents the Least Squares Regression Line  Commodity =85.175996+1.11437 Oil \text { Commodity }=85.175996+1.11437 \text { Oil }

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Question 27
Multiple Choice
arrowQuestion 27arrow
Multiple Choice

The following MINITAB output presents the least squares regression line for predicting the price of a certain commodity from the price of a barrel of oil.

The regression equation is
 Commodity =85.175996+1.11437 Oil \text { Commodity }=85.175996+1.11437 \text { Oil }
 Predictor  Coef  SE Coef  T  P  Constant 85.17599667.2943331.2657230.274315 Oil 1.114370.6665361.6718820.169866\begin{array}{lrrrr}\text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\\text { Constant } & 85.175996 & 67.294333 & 1.265723 & 0.274315 \\\text { Oil } & 1.11437 & 0.666536 & 1.671882 & 0.169866\end{array}

Write the equation of the least-squares regression line.


A) y=85.175996+1.11437xy = 85.175996 + 1.11437 x
B) y=1.265723+1.671882xy = 1.265723 + 1.671882 x
C) y=0.274315+0.169866xy = 0.274315 + 0.169866 x
D) y=1.11437+85.175996xy = 1.11437 + 85.175996 x

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