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Regression Analysis: U.S. general aviation shipments

Instructions: For each exercise, use Excel, MegaStat, or MINITAB to make an attractive, well-labeled time-series line chart. Adjust the Y-axis scale if necessary to show more detail (since Excel usually starts the scale at zero). If a fitted trend is called for, use Excel's option to display the equation and R2 statistic (or MAPE, MAD, and MSD in MINITAB). Include printed copies of all relevant graphs with your answers to each exercise.

14.16 (a) Plot the data on U.S. general aviation shipments.
(b) Describe the pattern and discuss possible causes.
(c) Would a fitted trend be helpful? Explain.
(d) Make a similar graph for 1992-2003 only. Would a fitted trend be helpful in making a prediction for 2004?
(e) Fit a trend model of your choice to the 1992-2003 data.
(f) Make a forecast for 2004, using either the fitted trend model or a judgment forecast. Why is it best to ignore earlier years in this data set? Airplanes

U.S. Manufactured General Aviation Shipments, 1966-2003

Year Planes Year Planes Years Planes Years Planes
1966 15,587 1976 15,451 1986 1,495 1996 1,053
1967 13,484 1977 16,904 1987 1,085 1997 1,482
1968 13,556 1978 17,811 1988 1,143 1998 2,115
1969 12,407 1979 17,048 1989 1,535 1999 2,421
1970 7,277 1980 11,877 1990 1,134 2000 2,714
1971 7,346 1981 9,457 1991 1,021 2001 2,538
1972 9,774 1982 4,266 1992 856 2002 2,169
1973 13,646 1983 2,691 1993 870 2003 2,090
1974 14,166 1984 2,431 1994 881
1975 14,056 1985 2,029 1995 1,028

Source: U.S. Manufactured General Aviation Shipments, Statistical Databook 2003, General Aviation Manufacturers Association, used with permission.

Solution Summary

The solution provides step by step method for the regression analysis on U.S. general aviation shipments. Formula for the calculation and Interpretations of the results are also included.

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