The dataset shows US Gross Domestic Product (in billions of dollars) and Domestic Revenue Passenger Miles (in billions) for the years 2005 through 2018.Below this table is the MS Excel Summary Output regressing RPMs against RGDP.Next, interpret the regression output and explain the regression statistics.Be certain that the regression coefficients match those in the scatter plot equation.Finally, use the regression equation to predict RPMs for 2020 and 2021 assuming GDP falls by 5% in 2020 and then grows by 4% in 2021 each year from 2015. Instructions for building the scatter plot are at the end of the problem set

billions billions Year RGDP RPM 2005 14771 779 2006 15267 797 2007 15493 829 2008 15671 812 2009 15155 769 2010 15415 798 2011 15712 814 2012 16129 823 2013 16382 840 2014 16616 862 2015 17277 902 2016 17556 933 2017 17925 964 2018 18438 1011SUMMARY OUTPUT Regression Statistics Multiple F 0.978059 R Square 0.956599 Adjusted | 0.952982 Standard | 15.87741 Observati 14 ANOVA df SS MS F gnificance F Regressio 1 66676.11 66676.11 264.4909 1.54E-09 Residual 12 3025.107 252.0923 Total 13 69701.21 Coefficier Standard It Stat P-value Lower 95% Upper 95% Lower 95.( Upper 95.( Intercept -173.963 63.24949 -2.75042 0.017589 -311.772 -36.154 -311.772 -36.154 RGDP 0. 063073 0.003878 16.26318 1.54E-09 0.054623 0.071523 0.054623 0.071523