A prediction equation for starting salaries in $1,000s) and SAT scores was performed using simple linear regression. In the regression printout shown below, what can be said about the level of significance for the overall model? SUMMARY OUTPUT Regression Statistics Multiple R 0.935018123 R Square 0.87425889 Adjusted R Square 0.860287655 Standard Error 3.307295949 Observations 11 ANOVA df Regression Residual Total 1 9 10 SS MS F Significance F 684.4652324 684 4652 62.57564 2.42144E-05 98.44385847 10.93821 782 9090909 Intercept SAT Coefficients Standard Error Stat P.value Lower 95% -29.14060468 8.660080997 -3.36493 0.008324 -48.73108387 0.065443841 0.008273059 7.910476 2.42E-05 0.046728866 Select one: A. The significance level for the intercept indicates the model is not valid B. The significance level for SAT indicates the slope is not equal to zero. CSAT is not a good predictor for starting salety D. The significance level for SAT indicates the slope is equal to zero E None of the above