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It Is Desired to Build a Regression Model to Predict y=\mathrm { y } =

question 46

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It is desired to build a regression model to predict y=\mathrm { y } = the sales price of a single family home, based on the x1=\mathrm { x } _ { 1 } = size of the house and x2=\mathrm { x } _ { 2 } = the neighborhood the home is located in. The goal is to compare the prices of homes that are located in two different neighborhoods. The following model is proposed:
E(y) =β0+β1x1+β2x2E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 }
A regression model was fit and the following residual plot was observed.
 It is desired to build a regression model to predict  \mathrm { y } =  the sales price of a single family home, based on the  \mathrm { x } _ { 1 } =  size of the house and  \mathrm { x } _ { 2 } =  the neighborhood the home is located in. The goal is to compare the prices of homes that are located in two different neighborhoods. The following model is proposed:  E ( y )  = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 }  A regression model was fit and the following residual plot was observed.   Which of the following assumptions appears violated based on this plot? A)  The errors are normally distributed B)  The mean of the errors is zero C)  The errors are independent D)  The variance of the errors is constant Which of the following assumptions appears violated based on this plot?


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