Using 20 observations, the multiple regression model y - Bo + B1*1 + A2x2 + was estimated. A portion of the regression results is as follows: df 2 17 19 SS 2.12E+12 3.206+11 2.38E+12 Regression Residual Total MS 1.02E+12 1.88E+10 54.348 Significance | 4.12E-08 Intercept X1 x2 Coefficienta -987,656 29,387 30,973 Standard Error 130, 799 31,927 32,693 t Stat -7.551 0.920 0.947 p-Value 0.000 0.370 0.357 Lover 95: -1,263,618 -37, 973 -38,003 Upper 95 -711,694 96, 747 99,949 a. At the 5% significance level, are the predictor variables jointly significant? O Yes, since the p-value of the appropriate test is more than 0.05. No, since the p-value of the appropriate test is less than 0.05. O Yes, since the p-value of the appropriate test is less than 0.05. O No, since the p-value of the appropriate test is more than 0.05. b. At the 5% significance level, Is each predictor variable Individually significant? Yes, since both p-values of the appropriate test are less than 0.05. Yes, since both p-values of the appropriate test are more than 0.05. No, since both p-values of the appropriate test are not less than 0.05. No einen hath a. At the 5% significance level, are the predictor variables jointly significant? Yes, since the p-value of the appropriate test is more than 0.05. O No, since the p-value of the appropriate test is less than 0.05. Yes, since the p-value of the appropriate test is less than 0.05. O No, since the p-value of the appropriate test is more than 0.05. b. At the 5% significance level, is each predictor variable individually significant? O Yes, since both p-values of the appropriate test are less than 0.05. O Yes, since both p-values of the appropriate test are more than 0.05. O No, since both p-values of the appropriate test are not less than 0.05. O No, since both p-values of the appropriate test are not more than 0.05. c. What is the likely problem with this model? Multicollinearity since the standard errors are biased. O Multicollinearity since the predictor variables are individually and jointly significant O Multicollinearity since the predictor variables are individually significant but jointly insignificant O Multicollinearity since the predictor variables are individually insignificant but jointly significant