41. Use problem number 10 on page 10-30 to answer the following questions (a-j). a) Find b1 and interpret b) Find b0 and interpret c) Write the equation 2 d) Find r and interpret e) Find SST f) Find S e g) Construct the 95% confidence interval for the mean of y when x = 7 h) Construct the 95% confidence interval for the individual value of y when x = 9 i) What is the consumption of apple per person when consumer income is $500? j) Interpret and show that you understand this regression equation. (Significant weight will be given to this question) 42. The given computer printout is a regression model relating plane travelling. Given X, number of fuel consumed (in gallon) and Y, flying time (1,000 mile) has been developed. Please fill in the blank and answer the following questions (a-g). SUMMARY OUTPUT Regression Statistics Multiple R 0.877 R Square ______ Adjusted R Square ______ Standard Error ______ Observations ______ ANOVA Regression Residual Total Intercept Fuel Consumed (x) df SS MS F Significance F 1 18.937 ______ 0.010 ______ 5.712 18.937 _____ _ 6 24.649 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% -8.859 0.132 8.077 0.032 -1.097 4.071 0.323 0.010 ______ ______ 11.904 0.215 29.621 0.049 ______ ______ a) Write and interpret the estimated regression equation b) What is the number of observations c) Compute the F statistic and test the significance of the relationship at a .05 level of significance. d) Predict the flying time when the plane consumes 270 Gallons of gas e) What is the coefficient of determination and interpret it. f) What is the coefficient of correlation and interpret it. g) Interpret and show that you understand this computer printout. (Significant weight will be given to this question) 43. Giving the selling price of the dependent variable and house size, house age and are independent variables please fill in the table and answer the following questions (a-h). ( =0.05 SUMMARY OUTPUT Regression Statistics Multiple R 0.9571 R Square _____ Adjusted R Square 0.8932 Standard Error 6.8940 Observations _____ ANOVA df SS MS F Significance F Regression 3 5707.4385 _____ _____ 3.27814E-06 Residual 11 _____ 47.5270 Total Intercept _____ 6230.2360 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% -16.0580 19.0710 -0.8420 0.4177 -58.0331 25.9171 _____ 25.9171 House Size 4.1462 0.7512 5.5195 0.0002 2.4928 5.7995 2.4928 _____ House Age -0.2361 0.8812 -0.2679 0.7937 -2.1756 1.7035 _____ 1.7035 Area 4.8309 0.9011 5.3612 0.0002 2.8476 6.8141 2.8476 _____ a) Write and interpret the estimated regression equation b) What is the number of observations c) What percent of the variation is explained by the regression equation, please explain. d) What is the standard error of regression, please explain.? e) What is the variance of the slope coefficient of House size? f) Conduct a global test of hypothesis to determine if any of the regression coefficients are not zero. g) Conduct a test of hypothesis for each of the independent variables. Which one you would eliminate and why? h) Interpret and show that you understand this computer printout. (Significant weight will be given to this question) Bonus Solution #43 41. Giving the selling price of the dependent variable and house size, house age and are independent variables please fill in the table and answer the following questions (a-h). ( =0.05 SUMMARY OUTPUT Regression Statistics Multiple R 0.9571 R Square 0.9161 Adjusted R Square 0.8932 Standard Error 6.8940 Observations 15 ANOVA df SS MS F Significance F Regression 3 5707.4385 1902.4795 40.029 3.27814E-06 Residual 11 522.797 47.5270 Total 14 6230.2360 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% -16.0580 19.0710 -0.8420 0.4177 -58.0331 25.9171 _____ 25.9171 House Size 4.1462 0.7512 5.5195 0.0002 2.4928 5.7995 2.4928 _____ House Age -0.2361 0.8812 -0.2679 0.7937 -2.1756 1.7035 _____ 1.7035 Area 4.8309 0.9011 5.3612 0.0002 2.8476 6.8141 2.8476 _____ Intercept #42 42. The given computer printout is a regression model relating plane travelling. Given X, number of fuel consumed (in gallon) and Y, flying time (1,000 mile) has been developed. Please fill in the blank and answer the following questions (a-g). SUMMARY OUTPUT Regression Statistics Multiple R 0.877 __0.7683___ R Square _ Adjusted R ______ Square Standard Error ______ Observations __7____ ANOVA Regression df SS MS 1 18.937 18.937 __1.1424___ Residual Total ___5___ 6 5.712 F ___16.577__ _ 24.649 Coefficients Lower t Stat P-value Error (x) 0.010 _ Standard Intercept Fuel Consumed Significance F Upper Lower Upper 95% 95% 95.0% 95.0% -8.859 8.077 -1.097 0.323 ______ 11.904 29.621 ______ 0.132 0.032 4.071 0.010 ______ 0.215 0.049 ______ Bonus Solution #43 41. Giving the selling price of the dependent variable and house size, house age and are independent variables please fill in the table and answer the following questions (a-h). ( =0.05 SUMMARY OUTPUT Regression Statistics Multiple R 0.9571 R Square 0.9161 Adjusted R Square 0.8932 Standard Error 6.8940 Observations 15 ANOVA df SS MS F Significance F Regression 3 5707.4385 1902.4795 40.029 3.27814E-06 Residual 11 522.797 47.5270 Total 14 6230.2360 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% -16.0580 19.0710 -0.8420 0.4177 -58.0331 25.9171 _____ 25.9171 House Size 4.1462 0.7512 5.5195 0.0002 2.4928 5.7995 2.4928 _____ House Age -0.2361 0.8812 -0.2679 0.7937 -2.1756 1.7035 _____ 1.7035 Area 4.8309 0.9011 5.3612 0.0002 2.8476 6.8141 2.8476 _____ Intercept #42 42. The given computer printout is a regression model relating plane travelling. Given X, number of fuel consumed (in gallon) and Y, flying time (1,000 mile) has been developed. Please fill in the blank and answer the following questions (a-g). SUMMARY OUTPUT Regression Statistics Multiple R 0.877 __0.7683___ R Square _ Adjusted R ______ Square Standard Error ______ Observations __7____ ANOVA Regression df SS MS 1 18.937 18.937 __1.1424___ Residual Total ___5___ 6 5.712 F ___16.577__ _ 24.649 Coefficients Lower t Stat P-value Error (x) 0.010 _ Standard Intercept Fuel Consumed Significance F Upper Lower Upper 95% 95% 95.0% 95.0% -8.859 8.077 -1.097 0.323 ______ 11.904 29.621 ______ 0.132 0.032 4.071 0.010 ______ 0.215 0.049 ______