c. Find the corresponding regression equation. Does each variable (Bh and B2) significantly predict the price of the house? Justify your answer and report coefficients and p values for each variable. (7p) d. What is the predicted price for the house that has an extra full bath? (4p) e. What is the predicted price for the house that has an extra half bath? (4p) 5. Run the multiple regression analysis including all explanatory variables: Square Feet, the dummy variable Bed3, the dummy variables Bh and BZ. Excel Output (5p) a. What proportion of variance in the price of the house can be explained by the combination of all these explanatory variables? Is this proportion of variance statistically significant at .05 level of signicance? In other words, is the overall model statistically significant at .05 level of signicance? Justify your answer. (3 p) b. Find the corresponding regression equation. Does each variable (SqFt, Bed3, Bh and B2) significantly predict the price of the house? Justify your answer and report coefficients and p values for each variable. (14 p) c. Is there any variable in the data that does not significantly contribute to the model? If so, explain the reason for that and exclude the nonsignificant variable from the model and re- run the multiple regression analysis. (4 p) d. Do you observe any changes after excluding the variable in the model? Does the overall model fit the data well? Justify your answer and report the coefficient of determination for the model and the coefficient for each variable. Comment on the statistical significance of each variable. (Sp)