An analyst ran a regression for the last 60 months with the monthly returns for Procter and Gamble (PG) as the dependent variable and the monthly returns for the S&P 500 Index as the independent variable. The results are: Regression Statistics Multiple R 0.521185 R Square 0.271634 Adjusted R Squa 0.259076 Standard Error 0.04096 Observations 60 ANOVA df Regression Residual Total SS MS F gnificance 1 0.03629 0.03629 21.63032 1.96E-05 58 0.097309 0.001678 59 0.133599 Coefficientsandard Erri Stat P-value Lower 95% Upper 95%ower 95.0 pper 95.09 Intercept 0.003808 0.005288 0.72008 0.474368 -0.00678 0.014393 -0.00678 0.014393 X Variable 1 0.451966 0.097179 4.650841 1.96E-05 0.25744 0.646492 0.25744 0.646492 Based on this analysis, if the market return increases by 1.0%, the analyst would predict that PG's return would increase by: O A 0.52% OB. 0.27%. O C. 0.04%. OD. 0.45%