Is this model of a good model to assess the performance of Intel? So the company that was assigned to you is Intel with the ticker I NTC Intel. So the question here is that is this model the former French tractor model? Is it a good model?

 

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SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Regression Statistics Intercept MKT RF SMB HML 0.41730543 0.174143822 0.078852725 0.429267682 df 30 Coefficients -0.0231 1.0334 -0.1600 -0.1470 Port Std Port Ret Standard Error 0.0948 0.4845 0.8711 0.5614 MSFT KO GE INTC HD SS MS F 3 1.010260527 0.336753509 1.827493089 26 4.791039315 0.184270743 29 5.801299843 t Stat -0.2434 2.1328 0.300541538 0.133876705 -0.1836 -0.2618 Weight S 0.393831378 3.938313785 -0.00093556 -0.009355595 -0.408065124 -4.080651236 0.249938112 2.499381119 0.765231193 7.652311927 Significance F 0.166932022 P-value Lower 95% -0.2178 0.0375 -1.9505 -1.3009 0.8096 0.0425 0.8557 0.7955 Upper 95% 0.1717 2.0294 1.6306 1.0069 Lower 95.0% Upper 95.0% -0.2178 0.1717 0.0375 2.0294 -1.9505 1.6306 -1.3009 1.0069 SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Regression Statistics Intercept MKT RF SMB HML 0.41730543 0.174143822 0.078852725 0.429267682 df 30 Coefficients -0.0231 1.0334 -0.1600 -0.1470 Port Std Port Ret Standard Error 0.0948 0.4845 0.8711 0.5614 MSFT KO GE INTC HD SS MS F 3 1.010260527 0.336753509 1.827493089 26 4.791039315 0.184270743 29 5.801299843 t Stat -0.2434 2.1328 0.300541538 0.133876705 -0.1836 -0.2618 Weight S 0.393831378 3.938313785 -0.00093556 -0.009355595 -0.408065124 -4.080651236 0.249938112 2.499381119 0.765231193 7.652311927 Significance F 0.166932022 P-value Lower 95% -0.2178 0.0375 -1.9505 -1.3009 0.8096 0.0425 0.8557 0.7955 Upper 95% 0.1717 2.0294 1.6306 1.0069 Lower 95.0% Upper 95.0% -0.2178 0.1717 0.0375 2.0294 -1.9505 1.6306 -1.3009 1.0069

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The model you sent me is a multiple linear regression model It is a statistical model that is used t... View the full answer