Please ONLY ASNWER question 7 and 8 with accuracy and precision, appreciated!

Question Completion Status: QUESTION 3 The following information relates to Questions 3-8. Suppose a researcher collects data on houses that have been sold in a particular neighbourhood over the past year and obtains the regression results in the following table. Dependent variable: In(Price) Regressor (1) (2) (3) (4) (5) Size 0.00042 (0.000038) In(Size) 0.69 (0.054) 0.68 (0.087) 0.57 (2.03) 0.69 (0.055) [In(Size)] 0.0078 (0.14) Bedrooms 0.0036 (0.037) Pool 0.071 (0.034) 0.071 (0.034) 0.071 (0.036) 0.071 (0.035) 0.082 (0.032) 0.037 (0.029) View 0.027 (0.028) 0.026 (0.026) 0.027 (0.029) 0.027 (0.030) 0.0022 (0.10) Pool X View Condition 0.13 (0.045) 0.12 (0.035) 0.12 (0.035) 0.12 (0.036) 0.12 (0.035) Intercept 10.97 6.60 6.63 6.60 (0.069) (0.39) 7.02 (7.50) (0.53) (0.40) Click Save and Submit to save and submit Click Save All Answers to save all answers. Summary Statistics SER 0.1026 1.023 1.020 R2 0.0710 0.0761 0.0814 Variable definitions: Price sale price ($); Size house size (in square feet); Bedrooms number of bedrooms; Pool binary variable (1 if house has a swimming pool, 0 otherwise); View binary variable (1 if house has a nice view, 0 other- wise); Condition binary variable (1 if real estate agent reports house is in excellent condition, 0 otherwise). pletion QUESTION 5 Continue to use the information from Question 3. Using column (2), what is the estimated percentage effect of view on price? (Report your answer as a percentage to one decimal place, without a % sign) Construct a 99% confidence interval for the estimated percentage effect of view on price. The lower bound is: (Report your answer as a percentage to three decimal places, without a % sign) The upper bound is: (Report your answer as a percentage to three decimal places, without a % sign) (Type Yes or No) Is the effect of view on price statistically different from 0? Assume a 1% level of significance. QUESTION 6 Continue to use the information from Question 3. Using the regression results in column (3), calculate the estimated percentage effect of adding two bedrooms to a house. (Report your answer as a percentage to two decimal places, without a % sign) Is the effect of adding bedrooms statistically significant? Assume a 1% level of significance. (Type Yes or No) Which of the two variables - size or number of bedrooms - do you think is relatively more important in determining the price of a house? (Type Size if size is more important, or Bedrooms if bedrooms are more important). QUESTION 7 Continue to use the information from Question 3. Is the coefficient on Condition significant in column (4)... At the 1% level of significance? (Type Yes or No) At the 5% level of significance? (Type Yes or No) QUESTION 8 Continue to use the information from Question 3. Is the interaction term between Pool and View statistically significant at the 1% level in column (5)? (Type Yes or No) Find the percentage effect of adding a view on the price of a house with a pool. Find the per effect of adding a view on the price of a house without a pool. (Report both answers as a percentage to one decimal place, without a % sign.) Question Completion Status: QUESTION 3 The following information relates to Questions 3-8. Suppose a researcher collects data on houses that have been sold in a particular neighbourhood over the past year and obtains the regression results in the following table. Dependent variable: In(Price) Regressor (1) (2) (3) (4) (5) Size 0.00042 (0.000038) In(Size) 0.69 (0.054) 0.68 (0.087) 0.57 (2.03) 0.69 (0.055) [In(Size)] 0.0078 (0.14) Bedrooms 0.0036 (0.037) Pool 0.071 (0.034) 0.071 (0.034) 0.071 (0.036) 0.071 (0.035) 0.082 (0.032) 0.037 (0.029) View 0.027 (0.028) 0.026 (0.026) 0.027 (0.029) 0.027 (0.030) 0.0022 (0.10) Pool X View Condition 0.13 (0.045) 0.12 (0.035) 0.12 (0.035) 0.12 (0.036) 0.12 (0.035) Intercept 10.97 6.60 6.63 6.60 (0.069) (0.39) 7.02 (7.50) (0.53) (0.40) Click Save and Submit to save and submit Click Save All Answers to save all answers. Summary Statistics SER 0.1026 1.023 1.020 R2 0.0710 0.0761 0.0814 Variable definitions: Price sale price ($); Size house size (in square feet); Bedrooms number of bedrooms; Pool binary variable (1 if house has a swimming pool, 0 otherwise); View binary variable (1 if house has a nice view, 0 other- wise); Condition binary variable (1 if real estate agent reports house is in excellent condition, 0 otherwise). pletion QUESTION 5 Continue to use the information from Question 3. Using column (2), what is the estimated percentage effect of view on price? (Report your answer as a percentage to one decimal place, without a % sign) Construct a 99% confidence interval for the estimated percentage effect of view on price. The lower bound is: (Report your answer as a percentage to three decimal places, without a % sign) The upper bound is: (Report your answer as a percentage to three decimal places, without a % sign) (Type Yes or No) Is the effect of view on price statistically different from 0? Assume a 1% level of significance. QUESTION 6 Continue to use the information from Question 3. Using the regression results in column (3), calculate the estimated percentage effect of adding two bedrooms to a house. (Report your answer as a percentage to two decimal places, without a % sign) Is the effect of adding bedrooms statistically significant? Assume a 1% level of significance. (Type Yes or No) Which of the two variables - size or number of bedrooms - do you think is relatively more important in determining the price of a house? (Type Size if size is more important, or Bedrooms if bedrooms are more important). QUESTION 7 Continue to use the information from Question 3. Is the coefficient on Condition significant in column (4)... At the 1% level of significance? (Type Yes or No) At the 5% level of significance? (Type Yes or No) QUESTION 8 Continue to use the information from Question 3. Is the interaction term between Pool and View statistically significant at the 1% level in column (5)? (Type Yes or No) Find the percentage effect of adding a view on the price of a house with a pool. Find the per effect of adding a view on the price of a house without a pool. (Report both answers as a percentage to one decimal place, without a % sign.)