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It Is Desired to Build a Regression Model to Predict y=y =

Question 12

Multiple Choice

It is desired to build a regression model to predict y=y = the sales price of a single family home, based on the neighborhood the home is located in. The goal is to compare the prices of homes that are located in four different neighborhoods. Which regression model should be built?


A) E(y) =β0+β1x1\mathrm { E } ( \mathrm { y } ) = \beta _ { 0 } + \beta _ { 1 } \mathrm { x } _ { 1 } , where x1\mathrm { x } _ { 1 } is a qualitative variable that describes the four neighborhoods.
B) E(y) =β0+β1x1+β2x2+β3x3+β4x4\mathrm { E } ( \mathrm { y } ) = \beta _ { 0 } + \beta _ { 1 } \mathrm { x } _ { 1 } + \beta _ { 2 } \mathrm { x } _ { 2 } + \beta _ { 3 } \mathrm { x } _ { 3 } + \beta _ { 4 } \mathrm { x } _ { 4 } , where x1x4\mathrm { x } _ { 1 } - \mathrm { x } _ { 4 } are qualitative variables that describe the four neighborhoods.
C) E(y) =β0+β1x1+β2x2+β3x3\mathrm { E } ( \mathrm { y } ) = \beta _ { 0 } + \beta _ { 1 } \mathrm { x } _ { 1 } + \beta _ { 2 } \mathrm { x } _ { 2 } + \beta _ { 3 } \mathrm { x } _ { 3 } , where x1x3\mathrm { x } _ { 1 } - \mathrm { x } _ { 3 } are qualitative variables that describe the four neighborhoods.
D) E(y) =β0+β1x1+β2x12\mathrm { E } ( \mathrm { y } ) = \beta _ { 0 } + \beta _ { 1 } \mathrm { x } _ { 1 } + \beta _ { 2 } \mathrm { x } _ { 1 } ^ { 2 } , where x1\mathrm { x } _ { 1 } is a qualitative variable that describes the four neighborhoods.

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