This question relates to the NFL Problem. To investigate the importance of passing on the percentage of games won by a team, the NFL found the following regression output. Their model used the average number of yards per attempt (Yds/Att) to estimate the percentage of games won (% won). SUMMARY OUTPUT Regression Statistics Multiple R 0.986933243 R Square 0.974037227 Adjusted R Square 0.97079188 Standard Error 2.336102514 Observations 10 ANOVA df SS MS F Significance F Regression 1637.941 1637.941 300.1334917 1.25552E-07 Residual LD CO H 43.65899963 5.457374954 Total 1681.6 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 51.8 5.051195188 -10.24862365 7.06412E-06 -63.41587546 -40.11972147 - -63.41587546 -40.11972147 Yds/Att 12.2 0.705774373 17.32436122 1.25552E-07 10.59957156 13.8546088 10.59957156 13.8546088 The average number of passing yards per attempt for Team A was 7.3. Use the estimated regression equation to predict the percentage of games won by the team. Round your answer to the nearest percent. You do not need to include the % sign in your answer.This question relates to the NFL Problem. Based on the regression model for the NFL, we can make the following conclusion: [59'6\"] V % of the variability in the [59'6\"] V in our sample can be explained by the linear relationship between the average number of passing yards per attempt and the percentage of games won