A multiple regression model is run on a sample of data. Partial results are shown below. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept X1 X2 X3 X4 0.79904012 0.638465113 0.617506569 523.6196274 df 74 35 MS F 4 33409364.7 8352341.175 30.46323773 69 18918262.93 274177.7236 73 52327627.63 Stot P-value Coefficients Standard Error 56.95124803 180.3511585 -0.315779774 0.75312286 2.180080265 0.265362203 8.215489021 806611E-12 3.844861119 0.871388075 4.412340759 3.68285E-05 3.626209704 1.561744216 2.321897316 0.023196713 16.36166861 5.751501808 2.844764577 0.005844946 What is the probability the overall model is NOT significant? Significance F 1.31347E-14 Lower 95% Upper 95% Lower 95.0% Upper 95.0% 416,7419603 302.8394642-416.7419603 302.8394642 1.650697161 2.709463368 1.650697161 2.709463368 2.106489496 5.583232741 2.106489496 5.583232741 051061528 6.741804127 051061528 6.741804127 4.887736593 27.83560063 4.887736593 27.83560063