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A national homebulder builds single-family homes and condominium-style townhouses. The accompanying dataset provides information on the selling price, lot cost, and type of home for

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A national homebulder builds single-family homes and condominium-style townhouses. The accompanying dataset provides information on the selling price, lot cost, and type of home for closings during one month. Complete parts a through c. Click the icon to view the house sales data. a. Develop a multiple regression model for sales price as a function of lot cost and type of home without any interaction term. Create a dummy variable named "Townhouse", where it is equal to 1 when Type = "Townhouse" and 0 otherwise. Determine the coefficients of the regression equation. Sales Price =110,262+(3.68) Lot Cost (75,103) Townhouse (Round the constant and coefficient of Townhouse to the nearest integer as needed. Round all other values to two decimal places as needed.) b. Determine if an interaction exists between lot cost and type of home and find the best model. Use =0.1 as the level of significance. First determine whether an interaction exists. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. A. An interaction exists because the p-value of the variable Lot Cost is which is greater than . (Type an integer or a decimal rounded to three decimal places as needed.) B. An interaction exists because the p-value of the variable Townhouse is , which is greater than . (Type an integer or a decimal rounded to three decimal places as needed.) C. An interaction exists because the p-value of the variable Lot Cost - Townhouse is which is less than . (Type an integer or a decimal rounded to three decimal places as needed.) D. No interaction exists because the p-value is less than for all of the independent variables. A national homebulder builds single-family homes and condominium-style townhouses. The accompanying dataset provides information on the selling price, lot cost, and type of home for closings during one month. Complete parts a through c. Click the icon to view the house sales data. a. Develop a multiple regression model for sales price as a function of lot cost and type of home without any interaction term. Create a dummy variable named "Townhouse", where it is equal to 1 when Type = "Townhouse" and 0 otherwise. Determine the coefficients of the regression equation. Sales Price =110,262+(3.68) Lot Cost (75,103) Townhouse (Round the constant and coefficient of Townhouse to the nearest integer as needed. Round all other values to two decimal places as needed.) b. Determine if an interaction exists between lot cost and type of home and find the best model. Use =0.1 as the level of significance. First determine whether an interaction exists. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. A. An interaction exists because the p-value of the variable Lot Cost is which is greater than . (Type an integer or a decimal rounded to three decimal places as needed.) B. An interaction exists because the p-value of the variable Townhouse is , which is greater than . (Type an integer or a decimal rounded to three decimal places as needed.) C. An interaction exists because the p-value of the variable Lot Cost - Townhouse is which is less than . (Type an integer or a decimal rounded to three decimal places as needed.) D. No interaction exists because the p-value is less than for all of the independent variables

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