Business Analytics Question

The output from a regression model that was to predict sales based on the number of Radio and TV ads (x1) and Newspaper ads (x2) is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.7752 R Square 0.6010 Adjusted R Square 0.5589 Standard Error 229.4995 Observations 21 ANOVA df SS MS F Significance F Regression 2 1507061.915 753531 14.30663 0.000162085 Residual 18 1000730.676 52670.04 Total 20 2507792.591 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 319.75 226.01 1.41 0.17 153.30 792.80 -153.30 792.80 Radio&TV ads 14.15 2.81 5.03 0.00 3.26 20.04 8.26 20.04 Newspaper ads 8.25 5.61 1.47 0.16 3.49 20.0 -3.49 20.00 Select the following true statements. NOTE: You can select multiple statements if more than one is true. O The model would not be considered good because there is too high of a probability that the coefficient for Newspaper ads is zero. O The model would not be considered good because there is too high of a probability that the coefficient for Radio & TV ads is zero. The coefficient of determination is 0.6010. The coefficient of determination is 0.7752. O If I ran 10 Radio & TV ads and no Newspaper ads, I would expect sales to be $461.25. If I ran 10 Radio & TV ads and no Newspaper ads, I would expect sales to be $141.50. There were 21 observations in the data file. O There were 20 observations in the data file