An analyst working for a consulting firm develops a multiple regression model to forecast the gross profit margin on consulting projects. He runs a regression model with 5 predictor variables using a sample of 40 engagements. The output is attached. What proportion of the variability in engagement profit is explained by this model? SUMMARY OUTPUT Regression Statistics Multiple R 0.624479892 R Square 0.389975136 Adjusted R Square 0.320258009 Standard Error 425.3055965 Observations 40 ANOVA df Significance F 0.001371015 Regression Residual Total 4 35 39 SS MS F 4047246.169 1011811.5 5.593677636 6330969.764 180884.85 10378215.93 Coefficients Standard Error t Stat p.value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3167.41433 2840.54899 1.1150712 0.272418096 -2599.206659 8934.035319 -2599.206659 8934.035315 Proposal Bid 9.334602211 2.275358832 4.1024748 0.000231864 4.715378235 13.95382619 4.715378235 13.95382619 RFP 24.69911812 25.55233033 0.9666092 0.340371494 -27.17486994 76.57310618 -27.17486994 76.57310618 Previous work 29.78385539 14.9272416 1.9952685 0.053844426 -0.520055944 60.08776673 -0.520055944 60.0877667: Num of Competitors -78.37063672 55.88367301 -1.402389 0.16960705-191.8205236 35.07925021 - 191.8205236 35.0792502: O 39% 0.14% O 100% O 42.5% O 62% O 5.5%