(1) Are these betas consistent with your graph? Why?

(2) Based on t-test, are these betas statistically significant at 1% level of significance? Why? How about 5% level of significance and 10% level of significance and why?

(3) Now assume that you expect the return on the market will be 12% at the end of the month, what will be your best estimates of the expected return for your two chosen firms stocks according to your regression lines?

BETA REGRESSION SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.490644611 0.240732134 0.239102804 0.059401309 468 ANOVA df F Significance F 1.0137E-29 147.7491402 Regression Residual Total 1 1 466 467 SS MS 0.521335132 0.521335132 1.644288226 0.003528516 2.165623359 P-value Intercept S&P Index Returns Coefficients 0.011291731 0.772532981 Standard Error t Stat 0.002793975 4.041457955 0.063555706 12.15521041 Lower 95% 6.21334E-05 0.005801382 1.0137E-29 0.647641715 Upper 95% Lower 95.0% Upper 95.0% 0.01678208 0.005801382 0.016782081 0.89742425 0.647641715 0.897424248 SUMMARY OUTPUT Regression Statistics Multiple R Square Adjusted R Square Standard Error Observations 0.045040777 0.002028672 -0.000112898 0.091115336 468 ANOVA df F Significance F 0.33091687 0.947282671 Regression Residual Total SS MS 1 1 0.007864345 0.007864345 466 3.868734041 0.008302004 467 3.876598386 P-value Intercept S&P Index Returns Coefficients Standard Error t Stat 0.024368147 0.004285662 5.685970108 0.094883306 0.097487742 0.973284476 Lower 95% Upper 95% Lower 95.0% Upper 95.0% 2.2982E-08 0.015946531 0.03278976 0.015946531 0.032789764 0.33091687 -0.096686709 0.28645332 0.096686709 0.286453321 T-TEST t-Test: Two-Sample Assuming Unequal Variances t-Test: Two-Sample Assuming Unequal Variances WMT Returns 0.017569421 0.004637309 468 0.03659036 0.008065161 0.001872808 467 Mean Variance Observations Hypothesized Mean Difference df t Stat P(T