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
|