(Solved by Expert Tutors)The data are real US Gross Domestic Product (in billions of dollars)

• The data are real US Gross Domestic Product (in billions of dollars) and Domestic Revenue Passenger Miles (in millions) for the years 1996 through 2012. Below this table is the MS Excel Summary Output regressing RPMs against GDP. Using MS Excel or another similar application, build a scatter plot and insert the regression line and equation. 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 2013 and 2014 assuming GDP grows by 3% each year from 2012. You may wish to check the actual RPMs to see how closely your estimate matched. Note:? To build a scatter plot in Excel, select and copy the GDP and RPM data into Excel; select the data in Excel, then use Insert/Scatter to create a scatter plot. Finally, scroll down Chart Layout to select the format that creates a regression line and formula. Use the Excel Help function as needed.

 Year GDP RPM 1996 8,100.2 419.07 1997 8,608.5 438.42 1998 9,089.1 448.58 1999 9,665.7 472.96 2000 10,289.7 500.12 2001 10,625.3 472.60 2002 10,980.2 469.96 2003 11,512.2 492.73 2004 12,277.0 542.82 2005 13,095.4 569.24 2006 13,857.9 574.52 2007 14,480.3 592.33 2008 14,720.3 568.25 2009 14,417.9 538.98 2010 14,958.3 552.85 2011 15,533.8 563.65 2012 16,244.6 568.70

 SUMMARY OUTPUT Regression Statistics Multiple R 0.926457 R Square 0.858323 Adjusted R Square 0.848878 Standard Error 21.52755 Observations 17 ANOVA df SS MS F Significance F Regression 1 42114.69 42114.69 90.87497 9.342E-08 Residual 15 6951.532 463.4355 Total 16 49066.22 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 275.7148 25.82438 10.67653 2.1E-08 220.6713974 330.7581059 GDP 0.019662 0.002063 9.532837 9.34E-08 0.015265596 0.02405796

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This question was answered on: Apr 19, 2020

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