Question 27 i 1Point ) Referring to Table 3, what is the correct interpretation ofthe coefficient of multiple determination? G) 98.8% of the total variation in demand can be explained by the linear relationship between demand and price. 98.8% of the total variation in demand can be explained by the quadratic relationship between demand and price. 6:) 98.8% of the total variation in demand can be explained by the addition of the square term in price. 988% of the total variation in demand can be explained byjust the square term in price. Question 28 1 Point Referring to Table 3, does there appear to be significant upward curvature in the response curve relating the demand (Y) and the price (X) at 10% level of significance? A Yes, since the p-value for the test is less than 0. 10. B No, since the value of B is near 0. No, since the p-value for the test is greater than 0.10. D Yes, since the value of B is positive.Question 29 1 Point Referring to Table 3, a more parsimonious simple linear model is likely to be statistically superior to the fitted curvilinear for predicting sale price (Y). A True B FalseSUMMARY OUTPUT Regression Statistics Multiple R 0.994 R Square 0.988 Standard Error 12.42 Observations 12 ANDVA df SS MS F Signif F Regression 2 1 15145 57573 373 0.0001 Residual 9 1 388 1 54 Total 11 'I 16533 Coeff StdError t Stat pvalue Intercept 286.42 9.66 29.64 0.0001 Price 0.31 0.06 5.14 0.0006 Price Sq 0.000067 0.00007 0.95 0.3647 Referring to Table 3, what is the p-value associated with the test statistic for testing whether there is an upward curvature in the response curve relating the demand [Y] and the price [X]? G) None of the above