Refrigerator prices are affected by characteristics such as whether or not the refrigerator is on sale, whether or not it is listed as a Sub-Zero brand, the number of doors (one door or two doors), and the placement of the freezer compartment (top, side, or bottom). The table below shows the regression output from a regression model using the natural log of price as the dependent variable. The model was developed by the Bureau of Labor Statistics.  Variable Coefficient Standard Error t Statistic Intercept   5.2700   0.12679     41.56   Sale price   −0.0741   0.0239     −3.10   Sub-Zero brand   1.2056   0.1387     8.69   Total capacity (in cubic ft)   0.07588   0.00626     12.12   Two-door, freezer on bottom   0.05354   0.07222     0.74   Two-door, side freezer   Base             Two-door, freezer on top   −0.3031   0.03846     −7.88   One door with freezer   −0.7693   0.1337     −5.75   One door, no freezer   −0.8381   0.1529     −5.48       (a) Write the regression model, being careful to exclude the base indicator variable. (Negative amounts should be indicated by a minus sign. Round your answers to 4 decimal places.)   ln(Price) =  +  SalePrice +  Sub-Zero +  Capacity +  2DoorFzBot +  2DoorFzTop +  1DoorFz +  1DoorNoFz   (b) Find the p-value for each coefficient, using 302 degrees of freedom. Using an α = .01, which predictor variable(s) are not significant predictors? (Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.)    p-value SalePrice   Sub-Zero   Capacity   2DoorFzBot   2DoorFzTop   1DoorFz   1DoorNoFz      (c) By how much does the natural log of refrigerator price decrease from a two-door, side freezer model to a two-door, top freezer model? (Round your answer to 4 decimal places.) The natural log of the price decreases by

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Refrigerator prices are affected by characteristics such as whether or not the refrigerator is on sale, whether or not it is listed as a Sub-Zero brand, the number of doors (one door or two doors), and the placement of the freezer compartment (top, side, or bottom). The table below shows the regression output from a regression model using the natural log of price as the dependent variable. The model was developed by the Bureau of Labor Statistics.
 

Variable Coefficient Standard Error t Statistic
Intercept   5.2700   0.12679     41.56  
Sale price   −0.0741   0.0239     −3.10  
Sub-Zero brand   1.2056   0.1387     8.69  
Total capacity (in cubic ft)   0.07588   0.00626     12.12  
Two-door, freezer on bottom   0.05354   0.07222     0.74  
Two-door, side freezer   Base            
Two-door, freezer on top   −0.3031   0.03846     −7.88  
One door with freezer   −0.7693   0.1337     −5.75  
One door, no freezer   −0.8381   0.1529     −5.48  
 

 

(a) Write the regression model, being careful to exclude the base indicator variable. (Negative amounts should be indicated by a minus sign. Round your answers to 4 decimal places.)

 

ln(Price) =  +  SalePrice +  Sub-Zero +  Capacity +  2DoorFzBot +  2DoorFzTop +  1DoorFz +  1DoorNoFz

 

(b) Find the p-value for each coefficient, using 302 degrees of freedom. Using an α = .01, which predictor variable(s) are not significant predictors? (Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.)
 

  p-value
SalePrice  
Sub-Zero  
Capacity  
2DoorFzBot  
2DoorFzTop  
1DoorFz  
1DoorNoFz  
 

 
(c)
 By how much does the natural log of refrigerator price decrease from a two-doorside freezer model to a two-doortop freezer model(Round your answer to 4 decimal places.)
 
The natural log of the price decreases by            

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